Identification of polynucleotides for predicting activity of compounds that interact with and/or modulate protein tyrosine kinases and/or protein tyrosine kinase pathways in breast cells

ABSTRACT

The present invention describes polynucleotides that have been discovered to correlate to the relative sensitivity or resistance of cells, e.g., breast cell lines, to treatment with compounds that interact with and modulate, e.g., inhibit, protein tyrosine kinases, such as, for example, members of the Src family of tyrosine kinases, e.g., Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. These polynucleotides have been shown to have utility in predicting the resistance and sensitivity of breast cell lines to the compounds. Such polynucleotides comprise polynucleotide predictor or marker sets useful in methods of predicting drug response, and as prognostic or diagnostic indicators in disease management, particularly in those disease areas, e.g., breast cancer, in which signaling through one or more of the aforementioned Src tyrosine and protein tyrosine kinases is involved with the disease process.

This application is a continuation-in-part application of non-provisional application U.S. Ser. No. 10/648,593, filed Aug. 26, 2003, which claims benefit to provisional application U.S. Ser. No. 60/406,385, filed Aug. 27, 2002; under 35 U.S.C. 119(e).

FIELD OF THE INVENTION

The present invention relates generally to the field of pharmacogenomics, and more specifically to new and alternative methods and procedures to determine drug sensitivity in patients, and particularly in patients with breast cancer. This invention allows the development of individualized genetic profiles which aid in treating diseases and disorders based on patient response at a molecular level.

BACKGROUND OF THE INVENTION

Breast cancer is a disease with extensive histoclinical heterogeneity. Although conventional histological and clinical features have been correlated with prognosis, the same apparent prognostic type of breast tumors vary widely in their responsiveness to therapy and consequent survival of the patient. New prognostic and predictive markers are needed to accurately foretell a patient's response to drugs in the clinic. Such markers would facilitate the individualization of therapy for each patient.

The problem may be solved by the identification of new parameters that can better predict a patient's sensitivity to treatment or therapy. The classification of patient samples is a crucial aspect of cancer diagnosis and treatment. The association of a patient's response to drug treatment with molecular and genetic markers can open up new opportunities for drug development in non-responding patients, or distinguish a drug's indication among other treatment choices because of higher confidence in the efficacy. Further, the pre-selection of patients who are likely to respond well to a medicine, drug, or combination therapy may reduce the number of patients needed in a clinical study or accelerate the time needed to complete a clinical development program (M. Cockett et al., 2000, Current Opinion in Biotechnology, 11:602-609).

The major goal of pharmacogenomics research is to identify genetic markers that accurately predict a given patient's response to drugs in the clinic; such individualized genetic assessment would greatly facilitate personalized treatment. An approach of this nature is particularly needed in cancer treatment and therapy, where commonly used agents are ineffective in many patients, and side effects are frequent. The ability to predict drug sensitivity in patients is particularly challenging because drug responses reflect both the properties intrinsic to the target cells and also a host's metabolic properties. Efforts by those in the art to use genetic information to predict drug sensitivity have primarily focused on individual polynucleotides that have broad effects, such as the multidrug resistant polynucleotides, mdr1 and mrp1 (P. Sonneveld, 2000, J. Intern. Med., 247:521-534).

The development of microarray technologies for large scale characterization of polynucleotide expression pattern makes it possible to systematically search for multiple molecular markers and to categorize cancers into distinct subgroups that are not evident by traditional histopathological methods (J. Khan et al., 1998, Cancer Res., 58:5009-5013; A. A. Alizadeh et al., 2000, Nature, 403:503-511; M. Bittner et al., 2000, Nature, 406:536-540; J. Khan et al., 2001, Nature Medicine, 7(6):673-679; and T. R. Golub et al., 1999, Science, 286:531-537; U. Alon et al., 1999, Proc. Natl. Acad. Sci. USA, 96:6745-6750). Such technologies and molecular tools have made it possible to monitor the expression levels of a large number of transcripts within a cell at any given time (see, e.g., Schena et al., 1995, Science, 270:467-470; Lockhart et al., 1996, Nature Biotechnology, 14:1675-1680; Blanchard et al., 1996, Nature Biotechnology, 14:1649; and U.S. Pat. No. 5,569,588, issued Oct. 29, 1996 to Ashby et al.).

How differential polynucleotide expression is associated with health and disease is a basis of functional genomics, which is defined as the study of all of the polynucleotides expressed by a specific cell or a group of cells and the changes in their expression pattern during development, disease, or environmental exposure. Hybridization arrays, used to study polynucleotide expression, allow polynucleotide expression analysis on a genomic scale by permitting the examination of changes in expression of literally thousands of polynucleotides at one time. In general, for hybridization arrays, gene-specific sequences (probes) are immobilized on a solid state matrix. These sequences are then queried with labeled copies of nucleic acids from biological samples (targets). The underlying theory is that the greater the expression of a gene, the greater the amount of labeled target and thus, the greater output of signal. (W. M. Freeman et al., 2000, BioTechniques), 29:1042-1055).

Recent studies have demonstrated that polynucleotide expression information generated by microarray analysis of human tumors can predict clinical outcome (L. J. van't Veer et al., 2002, Nature, 415:530-536; M. West et al., 2001, Proc. Natl. Acad. Sci. USA, 98:11462-11467; T. Sorlie et al., 2001, Proc. Natl. Acad. Sci. USA, 98:10869-10874; M. Shipp et al., 2002, Nature Medicine, 8(1):68-74). These findings bring hope that cancer treatment will be vastly improved by better predicting the response of individual tumors to therapy.

Needed in the art are new and alternative methods and procedures to determine drug sensitivity in patients and which are necessary to treat diseases and disorders, particularly cancers such as breast cancer, based on patient response at a molecular level. By using cultured cells as a model of in vivo effects, the present invention advantageously focuses on cell-intrinsic properties that are exposed in cell culture and involves identified polynucleotides that correlate with drug sensitivity. The presently described discovery and identification of polynucleotides/marker polynucleotides (predictor polynucleotides and polynucleotide sets) in cell lines assayed in vitro can be used to correlate with drug responses in vivo, and thus can be extended to clinical situations in which the same polynucleotides are used to predict responses to drugs and/or chemotherapeutic agents by patients, with particular regard to breast cancer patients.

SUMMARY OF THE INVENTION

The present invention describes the identification of marker polynucleotides whose expression levels are highly correlated with drug sensitivity in breast cell lines that are either sensitive or resistant to protein tyrosine kinase inhibitor compounds. More particularly, the protein tyrosine kinases that are inhibited in accordance with the present invention include members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. For a review of these and other protein tyrosine kinases, see, for example, P. Blume-Jensen and T. Hunter, 2001, “Oncopolynucleotide Kinase Signaling”, Nature, 411:355-365. Some of these polynucleotides are also modulated by the tyrosine kinase inhibitor compounds, in particular, src tyrosine kinase inhibitor compounds, which indicates their involvement in the protein tyrosine kinase signaling pathway. These polynucleotides or “markers” show utility in predicting a host's response to a drug and/or drug treatment. Similar expression pattern of these polynucleotides to breast cell lines is also seen in primary breast tumors which indicates co-regulation of these marker polynucleotides.

It is an aspect of this invention to provide a cell culture model to identify polynucleotides whose expression levels correlate with drug sensitivity of cells associated with a disease state, or with a host having a disease. In accordance with the present invention, oligonucleotide microarrays were utilized to measure the expression levels of a large number of polynucleotides in a panel of untreated cell lines, particularly breast cell lines, for which drug sensitivity to a protein tyrosine kinase inhibitor compound was determined. The determination of the polynucleotide expression profiles in the untreated cells allowed a prediction of chemosensitivity and the identification of marker polynucleotides whose expression levels highly correlated with sensitivity to drugs or compounds that modulate, preferably inhibit, protein tyrosine kinase or the pathway in which the protein tyrosine kinase, e.g., src tyrosine kinase, is involved. The marker polynucleotides are thus able to be utilized as one or more predictors to foresee a patient's response to drugs or drug treatments that directly or indirectly affect protein tyrosine kinase activity.

It is another aspect of the present invention to provide a method of determining or predicting if an individual requiring drug or chemotherapeutic treatment or therapy for a disease state, or a cancer or tumor of a particular type, e.g., a breast cancer or breast tumor, will successfully respond or will not respond to the drug or chemotherapeutic treatment or therapy prior to the administration of such treatment or chemotherapy. Preferably, the treatment or therapy involves a protein tyrosine kinase modulating agent, e.g., an inhibitor of the protein tyrosine kinase activity. The protein tyrosine kinases whose activities can be inhibited by inhibitor compounds according to this invention include, for example, members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. Also in accordance with the present invention, cells from a patient tissue sample, e.g., a breast tumor or cancer biopsy, are assayed to determine their polynucleotide expression pattern prior to treatment with a protein tyrosine kinase modulating compound or drug, preferably a src tyrosine kinase inhibitor. The resulting polynucleotide expression profile of the test cells before exposure to the compound or drug is compared with the polynucleotide expression pattern of the predictor set of polynucleotides that have been described and shown herein (Table 2). In addition, in such a method, the polynucleotide expression pattern of one or more predictor polynucleotides, i.e., the sets of 40, 15 and 7 polynucleotides as set forth in Table 2, and Tables 4-5, respectively, and/or the set of 6 polynucleotides as set forth in Table 8, among other combinations, can also be used. These polynucleotides are derived from the control panel of the untreated cells that have been determined to be either resistant or sensitive to the drug or compound, i.e., FIG. 1 and Table 1.

Success or failure of treatment with a drug can be determined based on the polynucleotide expression pattern of cells from the test tissue (test cells), e.g., a tumor or cancer biopsy, as being relatively similar to or different from the polynucleotide expression pattern of the predictor set of polynucleotides. Thus, if the test cells show a polynucleotide expression profile which corresponds to that of the predictor set of polynucleotides in the control panel of cells which are sensitive to the drug or compound, it is highly likely or predicted that the individual's cancer or tumor will respond favorably to treatment with the drug or compound. By contrast, if the test cells show a polynucleotide expression pattern corresponding to that of the predictor set of polynucleotides of the control panel of cells which are resistant to the drug or compound, it is highly likely or predicted that the individual's cancer or tumor will not respond to treatment with the drug or compound.

It is a further aspect of this invention to provide screening assays for determining if a cancer patient will be susceptible or resistant to treatment with a drug or compound, particularly, a drug or compound directly or indirectly involved in a protein tyrosine kinase activity or a protein tyrosine kinase pathway. Such protein tyrosine kinases include, without limitation, members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors.

In a more particular aspect, the present invention provides screening assays for determining if a cancer patient will be susceptible or resistant to treatment with a drug or compound, particularly, a drug or compound directly or indirectly involved in src tyrosine kinase activity or the src tyrosine kinase pathway.

It is another aspect of the present invention to provide a method of monitoring the treatment of a patient having a disease treatable by a compound or agent that modulates a protein tyrosine kinase, including members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. This can be accomplished by comparing the resistance or sensitivity polynucleotide expression profile of cells from a patient tissue sample, e.g., a tumor or cancer biopsy, e.g., a breast cancer or tumor sample, prior to treatment with a drug or compound that inhibits the protein tyrosine kinase activity and again following treatment with the drug or compound. The isolated test cells from the patient's tissue sample are assayed to determine their polynucleotide expression pattern before and after exposure to a compound or drug, such as, e.g., a src tyrosine kinase inhibitor. The resulting polynucleotide expression profile of the test cells before and after treatment is compared with the polynucleotide expression pattern of the predictor set and subsets of polynucleotides that have been described and shown herein to be highly expressed in the control panel of cells that are either resistant or sensitive to the drug or compound. Thus, if a patient's response becomes one that is sensitive to treatment by a protein tyrosine kinase inhibitor compound, based on a correlation of the expression profile of the predictor polynucleotides, the patient's treatment prognosis can be qualified as favorable and treatment can continue. Also, if after treatment with a drug or compound, the test cells do not show a change in their polynucleotide expression profile that corresponds to the control panel of cells that are sensitive to the drug or compound, this can serve as an indicator that the current treatment should be modified, changed, or even discontinued. Such a monitoring process can indicate success or failure of a patient's treatment with a drug or compound, and the monitoring processes can be repeated as necessary or desired.

It is a further aspect of the present invention to provide predictor polynucleotides and predictor sets of polynucleotides having both diagnostic and prognostic value in disease areas in which signaling through a protein tyrosine kinase or a protein tyrosine kinase pathway is of importance, e.g., in cancers and tumors, in immunological disorders, conditions or dysfunctions, or in disease states in which cell signaling and/or proliferation controls are abnormal or aberrant. Such protein tyrosine kinases whose direct or indirect modulation can be associated with a disease state or condition, include members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. In accordance with this invention, the use of one or more predictor polynucleotides, or a predictor polynucleotide set or subset (such as the predictor polynucleotides of Table 2, the predictor polynucleotide subsets of Tables 4-5, and/or the set of 6 polynucleotides set forth in Table 8) is to forecast or foretell an outcome prior to having any knowledge about a biological system, or a cellular response.

It is yet another aspect of the present invention to assemble on or more polynucleotides, such as those listed in Table 2, the subset of polynucleotides as listed in Tables 4-5, or the set of 6 polynucleotides set forth in Table 8, that highly correlate with resistance or sensitivity to protein tyrosine kinase inhibitor drugs or compounds, into predictor polynucleotide sets, so as to predict, or reasonably foretell the effect of either the protein tyrosine inhibitor compounds, or compounds that affect the protein tyrosine kinase signaling pathway(s) in different biological systems, or for cellular responses. The predictor polynucleotide sets can be used in in vitro assays of drug response by test cells to predict in vivo outcome. In accordance with this invention, the various predictor polynucleotide sets described herein, or the combination of these predictor sets with other polynucleotides or other co-variants of these polynucleotides, can be used, for example, to predict how patients with cancer or a tumor might respond to therapeutic intervention with compounds that modulate protein tyrosine kinases, or modulate signaling through an entire protein tyrosine kinase regulatory pathway. The predictor sets of polynucleotides, or co-variants of these polynucleotides, can be used to predict how patients with a cancer or tumor respond to therapy employing compounds that modulate a tyrosine kinase, or the activity of a tyrosine kinase, such as protein tyrosine kinase members of the Src family, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors.

Another object of the present invention is to provide one or more specialized microarrays, e.g., oligonucleotide microarrays or cDNA microarrays, comprising those polynucleotides or combinations thereof, as described herein, showing expression profiles that correlate with either sensitivity or resistance to protein tyrosine kinase inhibitor compounds. Such microarrays can be employed in in vitro assays for assessing the expression level of the polynucleotides on the microarrays in the test cells from tumor biopsies, for example, and determining whether these test cells will be likely to be resistant or sensitive to the protein tyrosine kinase inhibitor compound(s). For example, a specialized microarray can be prepared using some or all of the polynucleotides, polynucleotide subsets, or combinations thereof, as described herein and shown in Tables 2, 4, 5, and/or 8. Cells from a tissue or organ biopsy can be isolated and exposed to one or more inhibitor compounds. Following application of nucleic acids isolated from both untreated and treated cells to one or more of the specialized microarrays, the pattern of polynucleotide expression of the tested cells can be determined and compared with that of the predictor polynucleotide pattern from the control panel of cells used to create the predictor polynucleotide set on the microarray. Based upon the polynucleotide expression pattern results from the cells undergoing testing, it can be determined if the cells show a resistant or a sensitive profile of polynucleotide expression. Whether or not the tested cells from a tissue or organ biopsy will respond to a protein tyrosine kinase inhibitor compound, and the course of treatment or therapy, can then be determined or evaluated based on the information gleaned from the results of the specialized microarray analysis.

It is a further aspect of the present invention to provide a kit for determining or predicting drug susceptibility or resistance by a patient having a disease, with particular regard to a cancer or tumor, namely, a breast cancer or tumor. Such kits are useful in a clinical setting for testing a patient's biopsied tumor or cancer sample, for example, to determine or predict if the patient's tumor or cancer will be resistant or sensitive to a given treatment or therapy with a drug, compound, chemotherapy agent, or biological agent that is directly or indirectly involved with modification, preferably, inhibition, of the activity of a protein tyrosine kinase or a cell signaling pathway involving protein tyrosine kinase activity. Provided in the kit are one or more microarrays, e.g., oligonucleotide microarrays or cDNA microarrays, comprising those polynucleotides that correlate with resistance and sensitivity to protein tyrosine kinase modulators, particularly, inhibitors of members of the Src family of protein tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as inhibitors of the Bcr-abl, Jak, PDGFR, c-kit and Eph receptors protein tyrosine kinases; and, in suitable containers, the modulator agents/compounds for use in testing cells from patient tissue specimens or patient samples; and instructions for use. In addition, kits contemplated by the present invention can include reagents or materials for the monitoring of the expression of the predictor or marker polynucleotides of the invention at the level of mRNA or protein, using other techniques and systems practiced in the art, e.g., RT-PCR assays, which employ primers designed on the basis of one or more of the predictor polynucleotides described herein, immunoassays, such as enzyme linked immunosorbent assays (ELISAs), immunoblotting, e.g., Western blots, or in situ hybridization, and the like, as further described herein. The kits according to the present invention can also comprise one or more predictor polynucleotides as set forth in Table 2, including subsets of predictor polynucleotides which include, but are not limited to the predictor polynucleotide subsets as presented in Tables 4-5, and/or 8 herein.

Another aspect of the present invention is to provide one or more polynucleotides among those of the predictor polynucleotides identified herein that can serve as targets for the development of drug therapies for disease treatment. Such targets can be particularly applicable to treatment of breast disease, such as breast cancers or tumors. Because these predictor polynucleotides are differentially expressed in sensitive and resistant cells, their expression pattern is correlated with the relative intrinsic sensitivity of cells to treatment with compounds that interact with and/or inhibit protein tyrosine kinases, including members of the Src family of protein tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as the Bcr-abl, Jak, PDGFR, c-kit and Eph receptors protein tyrosine kinases. Accordingly, the polynucleotides highly expressed in resistant cells can serve as targets for the development of new drug therapies for those tumors which are resistant to protein tyrosine kinase inhibitor compounds.

Yet another object of the present invention is to provide antibodies, either polyclonal or monoclonal, directed against one or more of the protein tyrosine kinase biomarker polypeptides, or peptides thereof, encoded by the predictor polynucleotides. Such antibodies can be used in a variety of ways, for example, to purify, detect, and target the protein tyrosine kinase biomarker polypeptides of the present invention, including both in vitro and in vivo diagnostic, detection, screening, and/or therapeutic methods, and the like. Included among the protein tyrosine kinase biomarker polypeptides of this invention are members of the Src family of protein tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as the Bcr-abl, Jak, PDGFR, c-kit and Eph receptors protein tyrosine kinases.

Yet another object of the present invention is to provide antisense reagents, including siRNA, RNAi, and ribozyme reagents, directed against one or more of the protein tyrosine kinase biomarker polypeptides, or peptides thereof, encoded by the predictor polynucleotides. Such antisense reagents can be used in a variety of ways, for example, to detect, to target, and inhibit the expression of the protein tyrosine kinase biomarker polypeptides of the present invention, including both in vitro and in vivo diagnostic, detection, screening, and/or therapeutic methods, and the like. Included among the protein tyrosine kinase biomarker polypeptides of this invention are members of the Src family of protein tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as the Bcr-abl, Jak, PDGFR, c-kit and Eph receptors protein tyrosine kinases.

The invention also relates to an antisense compound 8 to 30 nucleotides in length that specifically hybridizes to a nucleic acid molecule encoding the human protein tyrosine kinase biomarker polypeptides of the present invention, wherein said antisense compound inhibits the expression of the human protein tyrosine kinase biomarker polypeptides.

The invention further relates to a method of inhibiting the expression of the human protein tyrosine kinase biomarker polypeptides of the present invention in human cells or tissues comprising contacting said cells or tissues in vitro, or in vivo, with an antisense compound of the present invention so that expression of the protein tyrosine kinase biomarker polypeptides is inhibited.

The present invention is also directed to a method of identifying a compound that modulates the biological activity of protein tyrosine kinase biomarker polypeptides, comprising the steps of, (a) combining a candidate modulator compound with protein tyrosine kinase biomarker polypeptides in the presence of an antisense molecule that antagonizes the activity of the protein tyrosine kinase biomarker polypeptides selected from the group consisting of SEQ ID NO:534 thru 557, and (b) identifying candidate compounds that reverse the antagonizing effect of the peptide.

The present invention is also directed to a method of identifying a compound that modulates the biological activity of protein tyrosine kinase biomarker polypeptides, comprising the steps of, (a) combining a candidate modulator compound with protein tyrosine kinase biomarker polypeptides in the presence of a small molecule that antagonizes the activity of the protein tyrosine kinase biomarker polypeptides selected from the group consisting of SEQ ID NO:534 thru 557, and (b) identifying candidate compounds that reverse the antagonizing effect of the peptide.

The present invention is also directed to a method of identifying a compound that modulates the biological activity of protein tyrosine kinase biomarker polypeptides, comprising the steps of, (a) combining a candidate modulator compound with protein tyrosine kinase biomarker polypeptides in the presence of a small molecule that agonizes the activity of the protein tyrosine kinase biomarker polypeptides selected from the group consisting of SEQ ID NO:534 thru 557, and (b) identifying candidate compounds that reverse the agonizing effect of the peptide.

The present invention is also directed to a predictor set comprising a plurality of polynucleotides whose expression pattern is predictive of the response of cells to treatment with a compound that modulates protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the the polynucleotides are selected from the group consisting of: the polynucleotides provided in Table 2; the sensitive predictor polynucleotides provided in Table 2; and the resistant predictor polynucleotides provided in Table 2.

The present invention is also directed to a predictor set comprising a plurality of polynucleotides whose expression pattern is predictive of the response of cells to treatment with a compound that modulates protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the the polynucleotides are selected from the group consisting of: the polynucleotides provided in Table 2; the sensitive predictor polynucleotides provided in Table 2; and the resistant predictor polynucleotides provided in Table 2; wherein the plurality of polynucleotides comprise the number of polynucleotides selected from the group consisting of: at least about 1 polynucleotides; at least about 2 polynucleotides; at least about 3 polynucleotides; at least about 4 polynucleotides; at least about 5 polynucleotides; at least about 6 polynucleotides; at least about 7 polynucleotides; at least about 10 polynucleotides; at least about 15 polynucleotides; at least about 20 polynucleotides; at least about 25 polynucleotides; and at least about 30 polynucleotides.

The present invention is also directed to a predictor set comprising a plurality of polynucleotides whose expression pattern is predictive of the response of cells to treatment with a compound that modulates protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the the polynucleotides are selected from the group consisting of: the polynucleotides provided in Table 2; the sensitive predictor polynucleotides provided in Table 2; and the resistant predictor polynucleotides provided in Table 2; wherein the plurality of polynucleotides comprise the number of polynucleotides selected from the group consisting of: at least about 1 polynucleotides; at least about 2 polynucleotides; at least about 3 polynucleotides; at least about 4 polynucleotides; at least about 5 polynucleotides; at least about 6 polynucleotides; at least about 7 polynucleotides; at least about 10 polynucleotides; at least about 15 polynucleotides; at least about 20 polynucleotides; at least about 25 polynucleotides; and at least about 30 polynucleotides; wherein the plurality of polynucleotides comprise a member of the group consisting of: the polynucleotides provided in Table 3; the sensitive predictor polynucleotides provided in Table 3; the resistant predictor polynucleotides provided in Table 3; the polynucleotides provided in Table 4; the sensitive predictor polynucleotides provided in Table 4; the resistant predictor polynucleotides provided in Table 4; the polynucleotides provided in Table 5; the sensitive predictor polynucleotides provided in Table 5; the resistant predictor polynucleotides provided in Table 5; the polynucleotides provided in Table 8; the sensitive predictor polynucleotides provided in Table 8; and the resistant predictor polynucleotides provided in Table 8.

The present invention is also directed to a predictor set comprising a plurality of polynucleotides whose expression pattern is predictive of the response of cells to treatment with a compound that modulates protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the the polynucleotides are selected from the group consisting of: the polynucleotides provided in Table 2; the sensitive predictor polynucleotides provided in Table 2; and the resistant predictor polynucleotides provided in Table 2; wherein the plurality of polynucleotides comprise the number of polynucleotides selected from the group consisting of: at least about 1 polynucleotides; at least about 2 polynucleotides; at least about 3 polynucleotides; at least about 4 polynucleotides; at least about 5 polynucleotides; at least about 6 polynucleotides; at least about 7 polynucleotides; at least about 10 polynucleotides; at least about 15 polynucleotides; at least about 20 polynucleotides; at least about 25 polynucleotides; and at least about 30 polynucleotides; wherein the plurality of polynucleotides comprise a member of the group consisting of: the polynucleotides provided in Table 3; the sensitive predictor polynucleotides provided in Table 3; the resistant predictor polynucleotides provided in Table 3; the polynucleotides provided in Table 4; the sensitive predictor polynucleotides provided in Table 4; the resistant predictor polynucleotides provided in Table 4; the polynucleotides provided in Table 5; the sensitive predictor polynucleotides provided in Table 5; the resistant predictor polynucleotides provided in Table 5; the polynucleotides provided in Table 8; the sensitive predictor polynucleotides provided in Table 8; and the resistant predictor polynucleotides provided in Table 8; wherein wherein the compound is selected from the group consisting of: antisense reagents directed to said polynucleotides, or one or more members of the protein tyrosine kinase pathway; RNAi reagents directed to said polynucleotides, or one or more members of the protein tyrosine kinase pathway; antibodies directed against polypeptides encoded by said polynucleotides, or one or more members of the protein tyrosine kinase pathway; and small molecule compounds.

The present invention is also directed to a predictor set comprising a plurality of polynucleotides whose expression pattern is predictive of the response of cells to treatment with a compound that modulates protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the the polynucleotides are selected from the group consisting of: the polynucleotides provided in Table 2; the sensitive predictor polynucleotides provided in Table 2; and the resistant predictor polynucleotides provided in Table 2; wherein the plurality of polynucleotides comprise the number of polynucleotides selected from the group consisting of: at least about 1 polynucleotides; at least about 2 polynucleotides; at least about 3 polynucleotides; at least about 4 polynucleotides; at least about 5 polynucleotides; at least about 6 polynucleotides; at least about 7 polynucleotides; at least about 10 polynucleotides; at least about 15 polynucleotides; at least about 20 polynucleotides; at least about 25 polynucleotides; and at least about 30 polynucleotides; wherein the plurality of polynucleotides comprise a member of the group consisting of: the polynucleotides provided in Table 3; the sensitive predictor polynucleotides provided in Table 3; the resistant predictor polynucleotides provided in Table 3; the polynucleotides provided in Table 4; the sensitive predictor polynucleotides provided in Table 4; the resistant predictor polynucleotides provided in Table 4; the polynucleotides provided in Table 5; the sensitive predictor polynucleotides provided in Table 5; the resistant predictor polynucleotides provided in Table 5; the polynucleotides provided in Table 8; the sensitive predictor polynucleotides provided in Table 8; and the resistant predictor polynucleotides provided in Table 8; wherein wherein the compound is selected from the group consisting of: antisense reagents directed to said polynucleotides, or one or more members of the protein tyrosine kinase pathway; RNAi reagents directed to said polynucleotides, or one or more members of the protein tyrosine kinase pathway; antibodies directed against polypeptides encoded by said polynucleotides, or one or more members of the protein tyrosine kinase pathway; and small molecule compounds; wherein the compound is BMS-A.

A predictor set according to the present invention wherein said cells are a member of the group consisting of: cancer cells, breast cells, breast cancer cells, lung cells, lung cancer cells.

The present invention is also directed to a predictor set comprising a plurality of polypeptides whose expression pattern is predictive of the response of cells to treatment with compounds that modulate protein tyrosine kinase activity or members of the protein tyrosine kinase pathway.

The present invention is also directed to a predictor set comprising a plurality of polypeptides whose expression pattern is predictive of the response of cells to treatment with compounds that modulate protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the polypeptides are selected from the group consisting of: the polypeptides provided in Table 2; the sensitive predictor polypeptides provided in Table 2; and the resistant predictor polypeptides provided in Table 2.

The present invention is also directed to a predictor set comprising a plurality of polypeptides whose expression pattern is predictive of the response of cells to treatment with compounds that modulate protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the polypeptides are selected from the group consisting of: the polypeptides provided in Table 2; the sensitive predictor polypeptides provided in Table 2; and the resistant predictor polypeptides provided in Table 2; wherein the plurality of polypeptides comprise the number of polypeptides selected from the group consisting of: at least about 1 polypeptides; at least about 2 polypeptides at least about 3 polypeptides; at least about 4 polypeptides at least about 5 polypeptides; at least about 6 polypeptides at least about 7 polypeptides; at least about 10 polypeptides; at least about 15 polypeptides; at least about 20 polypeptides; at least about 25 polypeptides; and at least about 30 polypeptides.

The present invention is also directed to a predictor set comprising a plurality of polypeptides whose expression pattern is predictive of the response of cells to treatment with compounds that modulate protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the polypeptides are selected from the group consisting of: the polypeptides provided in Table 2; the sensitive predictor polypeptides provided in Table 2; and the resistant predictor polypeptides provided in Table 2; wherein the plurality of polypeptides comprise the number of polypeptides selected from the group consisting of: at least about 1 polypeptides; at least about 2 polypeptides at least about 3 polypeptides; at least about 4 polypeptides at least about 5 polypeptides; at least about 6 polypeptides at least about 7 polypeptides; at least about 10 polypeptides; at least about 15 polypeptides; at least about 20 polypeptides; at least about 25 polypeptides; and at least about 30 polypeptides; wherein the plurality of polypeptides comprise a member of the group consisting of: polypeptides provided in Table 3; the sensitive predictor polypeptides provided in Table 3; the resistant predictor polypeptides provided in Table 3; the polypeptides provided in Table 4; the sensitive predictor polypeptides provided in Table 4; the resistant predictor polypeptides provided in Table 4; the polypeptides provided in Table 5; the sensitive predictor polypeptides provided in Table 5; the resistant predictor polypeptides provided in Table 5; the polypeptides provided in Table 8; the sensitive predictor polypeptides provided in Table 8; and the resistant predictor polypeptides provided in Table 8.

The present invention is also directed to a predictor set comprising a plurality of polypeptides whose expression pattern is predictive of the response of cells to treatment with compounds that modulate protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the polypeptides are selected from the group consisting of: the polypeptides provided in Table 2; the sensitive predictor polypeptides provided in Table 2; and the resistant predictor polypeptides provided in Table 2; wherein the plurality of polypeptides comprise the number of polypeptides selected from the group consisting of: at least about 1 polypeptides; at least about 2 polypeptides at least about 3 polypeptides; at least about 4 polypeptides at least about 5 polypeptides; at least about 6 polypeptides at least about 7 polypeptides; at least about 10 polypeptides; at least about 15 polypeptides; at least about 20 polypeptides; at least about 25 polypeptides; and at least about 30 polypeptides; wherein the plurality of polypeptides comprise a member of the group consisting of: polypeptides provided in Table 3; the sensitive predictor polypeptides provided in Table 3; the resistant predictor polypeptides provided in Table 3; the polypeptides provided in Table 4; the sensitive predictor polypeptides provided in Table 4; the resistant predictor polypeptides provided in Table 4; the polypeptides provided in Table 5; the sensitive predictor polypeptides provided in Table 5; the resistant predictor polypeptides provided in Table 5; the polypeptides provided in Table 8; the sensitive predictor polypeptides provided in Table 8; and the resistant predictor polypeptides provided in Table 8; wherein the compound is selected from the group consisting of: antisense reagents directed against polynucleotides encoding said polypeptides, or one or more members of the protein tyrosine kinase pathway; antibodies directed against said polypeptides, or one or more members of the protein tyrosine kinase pathway; and small molecule compounds.

The present invention is also directed to a predictor set comprising a plurality of polypeptides whose expression pattern is predictive of the response of cells to treatment with compounds that modulate protein tyrosine kinase activity or members of the protein tyrosine kinase pathway; wherein the polypeptides are selected from the group consisting of: the polypeptides provided in Table 2; the sensitive predictor polypeptides provided in Table 2; and the resistant predictor polypeptides provided in Table 2; wherein the plurality of polypeptides comprise the number of polypeptides selected from the group consisting of: at least about 1 polypeptides; at least about 2 polypeptides at least about 3 polypeptides; at least about 4 polypeptides at least about 5 polypeptides; at least about 6 polypeptides at least about 7 polypeptides; at least about 10 polypeptides; at least about 15 polypeptides; at least about 20 polypeptides; at least about 25 polypeptides; and at least about 30 polypeptides; wherein the plurality of polypeptides comprise a member of the group consisting of: polypeptides provided in Table 3; the sensitive predictor polypeptides provided in Table 3; the resistant predictor polypeptides provided in Table 3; the polypeptides provided in Table 4; the sensitive predictor polypeptides provided in Table 4; the resistant predictor polypeptides provided in Table 4; the polypeptides provided in Table 5; the sensitive predictor polypeptides provided in Table 5; the resistant predictor polypeptides provided in Table 5; the polypeptides provided in Table 8; the sensitive predictor polypeptides provided in Table 8; and the resistant predictor polypeptides provided in Table 8; wherein the compound is selected from the group consisting of: antisense reagents directed against polynucleotides encoding said polypeptides, or one or more members of the protein tyrosine kinase pathway; antibodies directed against said polypeptides, or one or more members of the protein tyrosine kinase pathway; and small molecule compounds; wherein the compound is BMS-A.

The present invention is also directed to a method for predicting whether a compound is capable of modulating the activity of cells, comprising the steps of: obtaining a sample of cells; determining whether said cells express a plurality of markers; and correlating the expression of said markers to the compounds ability to modulate the activity of said cells.

The present invention is also directed to a method for predicting whether a compound is capable of modulating the activity of cells, comprising the steps of: obtaining a sample of cells; determining whether said cells express a plurality of markers; and correlating the expression of said markers to the compounds ability to modulate the activity of said cells wherein the plurality of markers are polynucleotides.

The present invention is also directed to a method for predicting whether a compound is capable of modulating the activity of cells, comprising the steps of: obtaining a sample of cells; determining whether said cells express a plurality of markers; and correlating the expression of said markers to the compounds ability to modulate the activity of said cells wherein the plurality of markers are polynucleotides; wherein the polynucleotides, compounds, and cells are the polynucleotides, compounds, and cells disclosed herein.

The present invention is also directed to a method for predicting whether a compound is capable of modulating the activity of cells, comprising the steps of: obtaining a sample of cells; determining whether said cells express a plurality of markers; and correlating the expression of said markers to the compounds ability to modulate the activity of said cells wherein the plurality of markers are polypeptides.

The present invention is also directed to a plurality of cell lines for identifying polynucleotides and polypeptides whose expression levels correlate with compound sensitivity or resistance of cells associated with a disease state; wherein said cell lines are breast cancer cell lines, or lung cancer cell lines.

The present invention is also directed to a method of identifying polynucleotides and polypeptides that predict compound sensitivity or resistance of cells associated with a disease state, comprising the steps of: subjecting the plurality of cell lines of the present invention to one or more compounds; analyzing the expression pattern of a microarray of polynucleotides or polypeptides; and selecting polynucleotides or polypeptides that predict the sensitivity or resistance of cells associated with a disease state by using said expression pattern of said microarray; wherein said compounds are compounds disclosed herein, and wherein said disease is breast cancer, and/or lung cancer.

The present invention is also directed to a method for predicting whether an individual requiring treatment for a disease state, will successfully respond or will not respond to said treatment comprising the steps of: obtaining a sample of cells from said individual; determining whether said cells express a plurality of markers; and correlating the expression of said markers to the individuals ability to respond to said treatment.

The present invention is also directed to a method for predicting whether an individual requiring treatment for a disease state, will successfully respond or will not respond to said treatment comprising the steps of: obtaining a sample of cells from said individual; determining whether said cells express a plurality of markers; and correlating the expression of said markers to the individuals ability to respond to said treatment; wherein the plurality of markers are polynucleotides; wherein the polynucleotides, and compounds are disclosed herein.

The present invention is also directed to a method for predicting whether an individual requiring treatment for a disease state, will successfully respond or will not respond to said treatment comprising the steps of: obtaining a sample of cells from said individual; determining whether said cells express a plurality of markers; and correlating the expression of said markers to the individuals ability to respond to said treatment; wherein the plurality of markers are polypeptides; wherein the polypeptides, and compounds are disclosed herein.

The present invention is also directed to a method of screening for candidate compounds capable of binding to and/or modulating the activity of a protein tyrosine kinase biomarker polypeptide, comprising: contacting a test compound with a polypeptide described herein; and selecting as candidate compounds those test compounds that bind to and/or modulate activity of the polypeptide.

The present invention is also directed to a method of treating breast cancer in a subject, comprising administering a modulator of one or more protein tyrosine kinase biomarker polypeptides, wherein said polypeptide(s) is selected from the group consisting of: polypeptides provided in Table 2; the sensitive predictor polypeptides provided in Table 2; the resistant predictor polypeptides provided in Table 2; polypeptides provided in Table 3; the sensitive predictor polypeptides provided in Table 3; the resistant predictor polypeptides provided in Table 3; the polypeptides provided in Table 4; the sensitive predictor polypeptides provided in Table 4; the resistant predictor polypeptides provided in Table 4; the polypeptides provided in Table 5; the sensitive predictor polypeptides provided in Table 5; the resistant predictor polypeptides provided in Table 5; the polypeptides provided in Table 8; the sensitive predictor polypeptides provided in Table 8; and the resistant predictor polypeptides provided in Table 8.

Further aspects, features, and advantages of the present invention will be better appreciated upon a reading of the detailed description of the invention when considered in connection with the accompanying figures or drawings.

DESCRIPTION OF THE FIGURES

The file of this patent contains at least one Figure executed in color. Copies of this patent with color Figure(s) will be provided by the Patent and Trademark Office upon request and payment of the necessary fee.

FIG. 1 illustrates a polynucleotide expression pattern according to the present invention. The 137 polynucleotides that highly correlated with a resistance/sensitivity phenotype classification of the 23 breast cell lines for the protein tyrosine kinase inhibitor compound BMS-A are shown. Each row corresponds to a polynucleotide, with the columns corresponding to expression level in the different cell lines. Expression levels for each polynucleotide were normalized across all 23 breast cell lines such that the median is 0 and the standard derivation is 1. The expression levels greater than the median are shaded in red, those below the mean are shaded in green, while those at the mean are shaded in black. The individual polynucleotides encoding the protein tyrosine kinase biomarkers of the invention are indicated at the right (details of the biomarkers are also shown in the Table 2). The cell lines have been classified as being sensitive or resistant to BMS-A according to their IC₅₀ as provided in Table 1.

FIG. 2 The examples of polynucleotides whose expression levels are not only correlated with the sensitivity or resistance of breast cell lines to treatment with a protein tyrosine kinase inhibitor compound (e.g., BMS-A), but also differentially down regulated by treatment with the compound. Eleven breast cell lines (5 sensitive and 6 resistant cell lines as indicated in bold in the Table 1) were used in a drug treatment study. Cells were treated with or without the BMS-A compound (0.4 μM) in 0.1% DMSO for 24 hours. Expression profiling was performed, the polynucleotide expression of a cell line treated with drug was compared pair-wisely to the polynucleotide expression of the same cell line without drug treatment. Five sensitive cell lines without drug treatment are indicated with lightly shaded bars (“A” side of graph); five sensitive cell lines with drug treatment are indicated in darkly shaded bars (“A” side of graph); six resistant cell lines without drug treatment are indicated in darkly shaded bars (“B” side of graph); six resistant cell lines with drug treatment are indicated in lightly shaded bars (“B” side of graph).

FIG. 3 The examples of polynucleotide whose expression is down regulated by BMS-A compound treatment in a dose and time dependent manner in a prostate cell line PC3. Cells are treated without or with 0.025 μM, 0.1 μM and 0.4 μM of the BMS-A compound for 4 hours or 24 hours. The relative polynucleotide expression level of treated cells is compared to the corresponding untreated control which is set to 1. Drug concentrations and time of treatment are indicated.

FIG. 4 Immunoblot analysis of EphA2 protein level and tyrosine phosphorylation status in nine breast tumor cell lines. Cells were treated with 0.1 μM BMS-A for 1 hour. Cell lysates were immuno-precipitated with EphA2 antibody and blotted with EphA2 antibody (to assess EphA2 protein level) or anti-phosphotyrosine antibody (to assess EphA2 tyrosine phosphorylation status). Cell lines with or without drug treatment are indicated. The results indicate that EphA2 protein level does not change upon one hour drug treatment, but the phosphorylation of tyrosine residues is dramatically decreased with the drug treatment.

FIG. 5 shows the error rates of different predictor sets comprising the marker polynucleotides with differential selection and combination for the BMS-A protein tyrosine kinase inhibitor compound in the leave-one-out cross validation tests. The Genecluster software was used to select polynucleotides and predict classifications using a “weighted-voting leave-one-out cross-validation algorithm”, as described herein. A different number of polynucleotides was selected in the predictor set from (i) the 137 polynucleotides, or (ii) the 40 polynucleotides modulated by BMS-A treatment as shown in Table 2, for predicting resistant and sensitive classes to BMS-A in the breast cell lines. FIG. 5 demonstrates that a different selection and different combination of polynucleotides in a predictor set achieve different error rates in the leave-one-out cross validation. When the predictor sets were selected from 137 polynucleotides as shown in Table 2, the lowest error rate of 6.3% was achieved in the leave-one-out cross validation with 15 markers. Another predictor set comprised of 7 polynucleotides selected from the 40 polynucleotides that were modulated by the drug treatment achieved an error rate of 3.1%. These results indicate that polynucleotides which are not only correlated with drug sensitivity, but also modulated by the drug, can provide a better and more accurate prediction in a predictor set.

FIG. 6 shows the error rate comparison for predicting the sensitivity classification of compound BMS-A in the breast cell lines and random permutation tests in leave-one-out cross validation. When a predictor set contained either 7 or 15 polynucleotides selected from different polynucleotide groups, the error rate of the leave-one-out cross validation tests for predicting sensitivity of BMS-A in the 23 breast cell lines was 3.1% and 6.3% respectively. In contrast, the real error rates ranged from 30% to 83% when the same number of polynucleotides in a predictor set was used in 20 cases in which classification for the breast cell lines was randomly assigned. This result demonstrates that the error rate value for predicting sensitivity of BMS-A in the 23 breast cell lines is significantly lower than the error rate for predicting sensitivity for the 23 breast cell lines when their classification is randomly assigned in 20 cases.

FIG. 7 The expression pattern of the 137 marker polynucleotides in 134 primary breast tumors. These 137 polynucleotides are highly correlated with a resistance/sensitivity phenotype classification of the 23 breast cell lines for the protein tyrosine kinase inhibitor compound BMS-A according to the present invention (as shown in FIG. 1). Each row corresponds to a gene, with the columns corresponding to expression level in the different breast tumor samples. Expression levels for each polynucleotide were normalized across all 134 breast tumor samples such that the median is 0 and the standard derivation is 1. The expression levels greater than the median are shaded in red, those below the mean are shaded in green, while those at the mean are shaded in black. The order of individual polynucleotides encoding the protein tyrosine kinase biomarkers of the invention are the same as indicated in FIG. 1. The expression pattern clearly shows that a group of primary breast tumors (as indicated by the arrow) highly expressed sensitive markers of protein tyrosine kinase inhibitor compound of the invention. By contrast, another different group highly expressed resistant markers.

FIG. 8 Illustrates RNA expression level of Src and EphA2 in a lung cell line A549 that was transfected with either negative control oligos (NC-AS) or Src specific antisense oligos (Src-AS). All antisense oligonucleotides were provided by Sequitur Inc. Transfection was performed separately with each of two NC-AS oligos (NC-18029 and NC-18030) or each of three Src-AS oilgos (Src-AS-18025, Src-AS-18028 and Src-AS-18032) in triplicates for 24 hours. The Src and EphA2 expression level from each transfection were measured in triplicates by quantitative RT-PCR and normalized to the expression of GAPDH gene. The values represent the average of 18 RT-PCR reactions for negative controls (triplicate RT-PCR×3 transfection experiments×two NC-AS oligos) and 27 RT-PCR reactions for Src-AS oligos (triplicate RT-PCR×3 transfection experiments×three different Src-AS oligos). t-test was performed to evaluate the expression difference between NC-AS and Src-AS transfected cells for both Src and EphA2 genes.

FIG. 9A-D demonstrates the protein expression level of Src and CAV-1 in a Hela cell line transfected with either a non-specific negative control RNAi directed against GFP (GFP B), or five Src-specific RNAi reagents (“1-4” and “SP”, which is a smart pool of several RNAi's) for 48 hours. All RNAi reagents were made by Dharmacon, Inc. The sequences for RNAi reagents 1, 2, 3, and 4 are provided as SEQ ID NO:558, 559, 560 and 561, respectively. The smart pool RNAi is available from Dharmacon, Inc. (Cat. # M-003175-01). Total cell lysate was analyzed by Western blot using antibodies for Src (Cat.# 05-184, Upstate Biotechnology Inc.) and for PCNA (Cat.# 610665, BD Transduction, Inc) or antibodies for CAV-1 (Cat.# 610406, BD Transduction, Inc) and PCNA. The PCNA protein level was used as an internal control for protein loading, the level of Src or CAV-1 expression was normalized to the level of PCNA. The percentage of inhibition was calculated by comparing ratio of Src/PCNA or CAV-1/PCNA from each of Src-RNAi transfected cells to the ratio from the negative control, which was transfected by GFP B RNAi. FIG. 9A. Western blot demonstrating the expression of Src and PCNA. FIG. 9B. percentage of Src inhibition evaluated by the ratio of Src/PCNA in Src-RNAi transfected cells relative to the ratio of expression observed in negative control GFP B-RNAi transfected cells. FIG. 9C. Western blot shown CAV-1 and PCNA expression in Src-RNAi transfected cells. FIG. 9D. percentage of CAV-1 inhibition evaluated by the ratio of CAV-1/PCNA in Src-RNAi transfected cells relative to the ratio in negative control GFP B-RNAi transfected cells.

FIG. 10A-D Comparison of the expression pattern of selected predictor polynucleotide markers in 23 breast cell lines measured by both Affymetrix Genechip and quantitative RT-PCR. The RT-PCR was done in triplicates and the expression level of the selected 4 markers, EphA2 (A), EphB2 (B), Caveolin-1 (C), and Caveolin-2 (D) was normalized to the level of GAPDH gene. The X-axis represents 23 breast cancer cell lines ranked by increasing IC₅₀ as shown in Table 1. The Y-axis represents expression level of markers in each cell line relative to MDA-MB-157 (set to 1000) measured by Affymetrix GeneChip and quantitative RT-PCR.

FIG. 11A-B Representative IHC analysis demonstrating the protein expression pattern of EphA2 (A) and Caveolin-1 (B) in multiple breast cell lines (40× magnification). A cell array was constructed containing 5 cell lines and stained under the same conditions. Hematoxylin counterstain provides a blue nuclear stain to assess cell and tissue morphology. Positive staining is indicated by the presence of a brown chromogen. Both EphA2 and Caveolin-1 antibodies were from Santa Cruz Signal Transduction Lab (Cat #: sc-924 for EphA2 and sc-894 for CAV-1).

DESCRIPTION OF THE TABLES

Table 1 presents the resistance/sensitivity phenotype classification of the 23 breast cell lines for the protein tyrosine kinase inhibitor compound BMS-A based on IC₅₀ results. The IC₅₀ for each cell line was assessed in by MTS assays as described in Example 1 (Methods). The mean IC₅₀ values along with standard deviations (SD) were calculated from 2 to 5 individual determinations for each cell line as shown. The IC₅₀ unit is μM. The mean IC₅₀ for each cell line was log-transformed to log₁₀(IC₅₀) and the mean log₁₀(IC₅₀) across the 23 breast cell lines for BMS-A was calculated and used to normalize the IC₅₀ data for each cell line. The cell lines with a log₁₀(IC₅₀) below the mean log₁₀(IC₅₀) were defined as sensitive to the compound, while those having a log₁₀(IC₅₀) above the mean log₁₀(IC₅₀) were considered to be resistant. The cell lines presented in bold were used in the drug induction study as described herein.

TABLE 1 mean IC₅₀ (μM) Normalized # Cell Lines to BMS-A SD Log(IC₅₀) Log(IC₅₀) Classification 1 MDA-MB-157 0.0055 0.0035 −2.25924 −2.25405 Sensitive 2 MDA-MB-231 0.0095 0.0058 −2.02422 −2.03843 Sensitive 3 HCC1954 0.0242 0.0172 −1.61621 −1.66411 Sensitive 4 HCC70 0.0337 0.0160 −1.47214 −1.53193 Sensitive 5 BT-20 0.1652 0.1036 −0.78195 −0.89871 Sensitive 6 HCC1806 0.2194 0.1508 −0.65884 −0.78576 Sensitive 7 HS578T 0.6472 0.5885 −0.18898 −0.35469 Sensitive 8 HCC1419 2.5093 0.2280 0.399548 0.18525 Resistant 9 SK-BR-3 2.7534 0.8410 0.439867 0.22224 Resistant 10 AU-565 5.2399 3.2627 0.719322 0.47863 Resistant 11 HCC38 6.6327 3.1673 0.821688 0.57254 Resistant 12 BT-474 6.7375 4.1515 0.828502 0.57880 Resistant 13 MDA-MB-468 7.1258 4.0960 0.852833 0.60112 Resistant 14 HCC1428 7.2926 4.1436 0.862881 0.61034 Resistant 15 MDA-MB-435S 7.7800 2.3643 0.89098 0.63612 Resistant 16 H3396 8.1950 3.2549 0.91355 0.65682 Resistant 17 BT-549 9.0576 1.1419 0.957014 0.69670 Resistant 18 ZR-75-30 9.2632 0.5827 0.966762 0.70564 Resistant 19 MCF7 >9.5238 1.95E−07 0.978811 0.71670 Resistant 20 MCF7/Her2 >9.5238  1.8E−07 0.978811 0.71670 Resistant 21 MDA-MB-436 >9.5238 1.51E−07 0.978811 0.71670 Resistant 22 ZR-75-1 >9.5238  1.8E−07 0.978811 0.71670 Resistant 23 MDA-MB-453 >9.5238 0.978811 0.71670 Resistant Mean IC₅₀ across 5.2744 0.197626 all 23 cell lines SD 3.9565 1.08998

Table 2 shows a polynucleotide list derived from three analysis algorithms that demonstrated a high correlation between expression pattern and resistance/sensitivity classification to BMS-A. The polynucleotide number, relative expression pattern, i.e., sensitive or resistant, Genbank Accession number, polynucleotide description, Unigene cluster number, SEQ ID NO: for the nucleic acid sequence of the gene, SEQ ID NO: for the amino acid sequence coded for by the polynucleotide (if available) and PID (protein ID), are presented in Table 2. For each gene, the DNA and encoded amino acid sequence represented by SEQ ID NOs. in Table 2 are set forth in the Sequence Listing.

TABLE 2 MARKERS HIGHLY CORRELATED TO BMS-A IN EXPRESSION PATTERN AND RESISTANCE/SENSITIVITY CLASSIFICATION Modu- DNA Amino Highly Genbank lated SEQ Acid Gene Expressed Accession by Unigene ID SEQ ID Protein No. in # BMS-A Unigene Title Cluster NO: NO: ID 1 Sensitive cells NM_004431 yes EphA2 Hs.171596 1 138 NP_004422 2 Sensitive cells AF025304 EphB2 Hs.125124 2 139 AAB94602 3 Sensitive cells AU147399 yes caveolin 1, caveolae protein, 22 kD Hs.74034 3 140 NP_001744 4 Sensitive cells NM_001233 yes caveolin 2 Hs.139851 4 141 NP_001224 5 Sensitive cells NM_000700 yes annexin A1 Hs.78225 5 142 NP_000691 6 Sensitive cells NM_004039 annexin A2 Hs.406239 6 143 NP_004030 7 Sensitive cells BG107577 parvin, alpha Hs.44077 7 144 Q9NVD7 8 Sensitive cells BE965369 yes coagulation factor II (thrombin) receptor-like 1 Hs.154299 8 145 XP_003671 9 Sensitive cells NM_001993 yes coagulation factor III (thromboplastin, tissue factor) Hs.62192 9 146 NP_001984 10 Sensitive cells BF792126 Homo sapiens, clone IMAGE: 4344858, mRNA Hs.432974 10 147 P1_453619 11 Sensitive cells BE856341 layilin Hs.133015 11 148 Q96NF3 12 Sensitive cells U17496 proteasome (prosome, macropain) subunit, beta type, 8 Hs.180062 12 149 P28062 (large multifunctional protease 7) 13 Sensitive cells NM_002800 proteasome (prosome, macropain) subunit, beta type, 9 Hs.381081 13 150 NP_002791 (large multifunctional protease 2) 14 Sensitive cells NM_000311 prion protein (p27-30) (Creutzfeld-Jakob disease, Hs.74621 14 151 P04156 Gerstmann-Strausler-Scheinker syndrome, fatal familial insomnia) 15 Sensitive cells NM_003739 yes aldo-keto reductase family 1, member C3 (3-alpha Hs.78183 15 152 NP_003730 hydroxysteroid debydrogenase, type II) 16 Sensitive cells NM_020639 ankyrin repeat domain 3 Hs.55565 16 153 NP_065690 17 Sensitive cells AF208043 yes interferon, gamma-inducible protein 16 Hs.155530 17 154 Q16666 18 Sensitive cells AF003837 yes jagged 1 (Alagille syndrome) Hs.91143 18 155 P78504 19 Sensitive cells BC002832 yes butyrophilin, subfamily 3, member A2 Hs.87497 19 156 AAF76140 20 Sensitive cells NM_006994 yes butyrophilin, subfamily 3, member A3 Hs.167741 20 157 NP_008925 21 Sensitive cells AF327443 calpastatin Hs.359682 21 158 XP_051211 22 Sensitive cells NM_021615 yes carbohydrate (N-acetylglucosamine 6-O) Hs.157439 22 159 NP_067628 sulfotransferase 6 23 Sensitive cells AF104857 yes CDC42 effector protein (Rho GTPase binding) 3 Hs.260024 23 160 NP_006440 24 Sensitive cells AL136896 suppressor of cytokine signaling 5 Hs.169836 24 161 O75159 25 Sensitive cells AL565621 yes coactosin-like protein Hs.289092 25 162 AAH16702 26 Sensitive cells BF111719 alkylglycerone phosphate synthase Hs.22580 26 163 O00116 27 Sensitive cells N36770 dual specificity phosphatase 10 Hs.177534 27 164 NP_009138 28 Sensitive cells AW575374 yes ELK3, ETS-domain protein (SRF accessory protein 2) Hs.288555 28 165 NP_005221 29 Sensitive cells AW269335 yes endothelial differentiation, lysophosphatidic acid G- Hs.75794 29 166 NP_001392 protein-coupled receptor, 2 30 Sensitive cells BC001247 yes epithelial protein lost in neoplasm beta Hs.10706 30 167 Q9UHB6 31 Sensitive cells BE669858 hypothetical protein FLJ39885 Hs.319825 31 168 NP_689916 32 Sensitive cells NM_000127 exostoses (multiple) 1 Hs.184161 32 169 NP_000118 33 Sensitive cells NM_002589 BH-protocadherin (brain-heart) Hs.34073 33 170 O60245 34 Sensitive cells AI133452 fibrinogen, gamma polypeptide Hs.75431 34 171 AAH21674 35 Sensitive cells NM_006101 highly expressed in cancer, rich in leucine heptad repeats Hs.58169 35 172 NP_006092 36 Sensitive cells AL135264 ESTs, Moderately similar to hypothetical protein Hs.406100 36 FLJ20489 37 Sensitive cells NM_014164 FXYD domain-containing ion transport regulator 5 Hs.333418 37 173 NP_054883 38 Sensitive cells BC003502 small fragment nuclease Hs.7527 38 174 Q9Y3B8 39 Sensitive cells AA780067 heparan sulfate (glucosamine) 3-O-sulfotransferase 3B1 Hs.159572 39 175 Q9Y662 40 Sensitive cells AA702248 yes Homo sapiens cDNA FLJ14241 fis, clone Hs.183765 40 OVARC1000533 41 Sensitive cells BC004372 CD44 antigen (homing function and Indian blood group Hs.169610 41 176 Q9UJ36 system) 42 Sensitive cells BF688144 Homo sapiens mRNA; cDNA DKFZp762O2215 (from Hs.331666 42 clone DKFZp762O2215) 43 Sensitive cells NM_018067 hypothetical protein FLJ10350 Hs.177596 43 177 NP_060537 44 Sensitive cells BG111761 guanine nucleotide binding protein (G protein), Hs.8107 44 178 Q9UBI6 gamma 12 45 Sensitive cells NM_017821 nucleoredoxin Hs.374534 45 179 NP_060291 46 Sensitive cells AA722799 endothelial and smooth muscle cell-derived neuropilin- Hs.173374 46 180 Q96PD2 like protein 47 Sensitive cells BC006436 hypothetical protein MGC13105 Hs.22744 47 181 AAH06436 48 Sensitive cells NM_006548 yes IGF-II mRNA-binding protein 2 Hs.30299 48 182 NP_006539 49 Sensitive cells NM_002194 inositol polyphosphate-1-phosphatase Hs.32309 49 183 NP_002185 50 Sensitive cells BG251556 KIAA1949 protein Hs.101150 50 184 BAB85535 51 Sensitive cells J03202 laminin, gamma 1 (formerly LAMB2) Hs.432855 51 185 NP_002284 52 Sensitive cells NM_000245 yes met proto-oncogene (hepatocyte growth factor receptor) Hs.316752 52 186 NP_000236 53 Sensitive cells NM_002444 moesin Hs.170328 53 187 NP_002435 54 Sensitive cells NM_012334 yes myosin X Hs.61638 54 188 NP_036466 55 Sensitive cells AI769569 ESTs Hs.112472 55 56 Sensitive cells NM_002633 yes phosphoglucomutase 1 Hs.1869 56 189 NP_002624 57 Sensitive cells BC004295 yes polymerase I and transcript release factor Hs.29759 57 190 O00535 58 Sensitive cells NM_016205 platelet derived growth factor C Hs.43080 58 191 Q9UL22 59 Sensitive cells NM_004815 yes PTPL1-associated RhoGAP 1 Hs.70983 59 192 NP_004806 60 Sensitive cells NM_002872 ras-related C3 botulinum toxin substrate 2 (rho family, Hs.301175 60 193 NP_002863 small GTP binding protein Rac2) 61 Sensitive cells AF329267 SH3-domain kinase binding protein 1 Hs.153260 61 194 XP_039010 62 Sensitive cells AI572079 snail homolog 2 (Drosophila) Hs.93005 62 195 AAH14890 63 Sensitive cells NM_001549 interferon-induced protein with tetratricopeptide repeats 4 Hs.181874 63 196 O14879 64 Sensitive cells D50683 transforming growth factor, beta receptor II (70-80 kD) Hs.82028 64 197 NP_003233 65 Sensitive cells NM_005902 MAD (mothers against decapentaplegic, Drosophila) Hs.288261 65 198 Q92940 homolog 3 66 Sensitive cells NM_014452 tumor necrosis factor receptor superfamily, member 21 Hs.159651 66 199 NP_055267 67 Sensitive cells AB017644 ubiquitin-conjugating enzyme E2E 3 (homologous to Hs.4890 67 200 XP_096160 yeast UBC4/5) 68 Sensitive cells BC002323 zyxin Hs.75873 68 201 Q15942 69 Resistant cells AL157452 Homo sapiens mRNA; cDNA DKFZp761C1712 (from Hs.4774 69 clone DKFZp761C1712) 70 Resistant cells BF752277 hypothetical protein FLJ20151 Hs.279916 70 202 Q9NXM9 71 Resistant cells BF512299 ESTs Hs.438672 71 72 Resistant cells AL049381 yes Homo sapiens mRNA; cDNA DKFZp586J2118 (from Hs.21851 72 clone DKFZp586J2118) 73 Resistant cells NM_002585 yes pre-B-cell leukemia transcription factor 1 Hs.155691 73 203 NP_002576 74 Resistant cells T68445 anaphase-promoting complex subunit 7 Hs.52763 74 204 Q96AC4 75 Resistant cells BF308645 PRex1 KIAA1415 protein Hs.109315 75 205 Q8TCU6 76 Resistant cells AF088867 yes anterior gradient 2 (Xenepus laevis) homolog Hs.413945 76 206 AF088867_1 77 Resistant cells NM_004040 yes Human HepG2 3′ region cDNA, clone hmd1f06. Hs.204354 77 207 NP_004031 78 Resistant cells AF151810 yes serologically defined colon cancer antigen 28 Hs.84700 78 208 Q9Y365 79 Resistant cells NM_004252 transmembrane 7 superfamily member 2 Hs.31130 79 209 NP_004243 80 Resistant cells NM_005749 yes transducer of ERBB2, 1 Hs.178137 80 210 NP_005740 81 Resistant cells NM_003225 yes trefoil factor 1 (breast cancer, estrogen-inducible Hs.350470 81 211 NP_003216 sequence expressed in) 82 Resistant cells AA181060 yes Homo sapiens cDNA FLJ31753 fis, clone Hs.349283 82 NT2RI2007468 83 Resistant cells AL050025 adaptor-related protein complex 1, gamma 1 subunit Hs.5344 83 212 CAB43244 84 Resistant cells NM_001089 ATP-binding cassette, sub-family A (ABC1), member 3 Hs.26630 84 213 NP_001080 85 Resistant cells NM_004915 ATP-binding cassette, sub-family G (WHITE), member 1 Hs.10237 85 214 NP_004906 86 Resistant cells AL523275 CALM1 calmodulin 1 (phosphorylase kinase, delta) Hs.374441 86 215 AAH00454 87 Resistant cells NM_001218 yes carbonic anhydrase XII Hs.5338 87 216 NP_001209 88 Resistant cells NM_016286 dicarbonyl/L-xylulose reductase Hs.9857 88 217 NP_057370 89 Resistant cells BC000185 carnitine palmitoyltransferase I, liver Hs.259785 89 218 AAH00185 90 Resistant cells NM_005505 scavenger receptor class B, member 1 Hs.180616 90 219 NP_005496 91 Resistant cells NM_016048 CGI-111 protein Hs.11085 91 220 NP_057132 92 Resistant cells BC000195 CGI-81 protein Hs.279583 92 221 NP_057109 93 Resistant cells NM_001306 claudin 3 Hs.25640 93 222 NP_001297 94 Resistant cells BC000021 cytochrome b-561 Hs.355264 94 223 NP_001906 95 Resistant cells W68084 EGF-like-domain, multiple 5 Hs.5599 95 224 Q9H1U4 96 Resistant cells AA825563 yes ESTs Hs.445708 96 97 Resistant cells BE887449 Homo sapiens cDNA FLJ34170 fis, clone Hs.32112 97 FCBBF3015396. 98 Resistant cells AI123815 yes hypothetical protein FLJ21963 Hs.13222 98 225 Q9H6R3 99 Resistant cells AI308862 RAB21, member RAS oncogene family Hs.184627 99 226 Q9UL25 100 Resistant cells AW006352 EST Hs.159643 100 101 Resistant cells AL554277 chromosome 17 open reading frame 28 Hs.11067 101 227 Q9NT34 102 Resistant cells BG289001 hypothetical protein LOC253782 Hs.387400 102 103 Resistant cells AI935915 hypothetical protein LOC112868 Hs.97837 103 228 XP_053402 104 Resistant cells NM_017689 yes hypothetical protein FLJ20151 Hs.279916 104 229 NP_060159 105 Resistant cells NM_017966 hypothetical protein FLJ20847 Hs.13479 105 230 NP_060436 106 Resistant cells AI923458 Williams Beuren syndrome chromosome region 21 Hs.182476 106 231 NP_112585 107 Resistant cells NM_000597 insulin-like growth factor binding protein 2 (36 kD) Hs.433326 107 232 NP_000588 108 Resistant cells U90304 iroquois homeobox protein 5 Hs.25351 108 233 P78411 109 Resistant cells NM_004968 islet cell autoantigen 1 (69 kD) Hs.167927 109 234 NP_004959 110 Resistant cells AL563283 androgen-induced basic leucine zipper Hs.372924 110 235 NP_570968 111 Resistant cells AA135522 KIAA0089 protein Hs.82432 111 236 AAH28726 112 Resistant cells AI867102 yes solute carrier family 9 (sodium/hydrogen exchanger), Hs.184276 112 237 XP_051621 isoform 3 regulatory factor 1 113 Resistant cells AWI34976 KIAA0984 protein Hs.11912 113 238 BAA76828 114 Resistant cells AW665865 KIAA1069 protein Hs.193143 114 239 BAA83021 115 Resistant cells AB051487 nucleoporin 210 Hs.270404 115 240 BAB40814 116 Resistant cells AB050049 methylcrotonoyl-Coenzyme A carboxylase 2 (beta) Hs.167531 116 241 Q9HCC0 117 Resistant cells NM_016835 microtubule-associated protein tau Hs.101174 117 242 NP_058519 118 Resistant cells AK002075 myelin gene expression factor 2 Hs.44268 118 243 NP_057216 119 Resistant cells NM_000933 Homo sapiens mRNA; cDNA DKFZp434E235 (from Hs.348724 119 244 NP_000924 clone DKFZp434E235) 120 Resistant cells AI435670 prostate epithelium-specific Ets transcription factor Hs.79414 120 245 NP_036523 121 Resistant cells NM_006443 putative c-Myc-responsive Hs.109752 121 246 NP_006434 122 Resistant cells AW263542 ESTs Hs.403937 122 AAH15948 123 Resistant cells AF153330 dual specificity phosphatase 16 Hs.20281 123 247 Q9BY84 124 Resistant cells BC002702 solute carrier family 25 (mitochondrial carrier; ornithine Hs.78457 124 248 Q9Y619 transporter) member 15 125 Resistant cells NM_006416 solute carrier family 35 (CMP-sialic acid transporter), Hs.82921 125 249 NP_006407 member 1 126 Resistant cells NM_030674 solute carrier family 38, member 1 Hs.18272 126 250 NP_109599 127 Resistant cells AF212371 spinster-like protein Hs.379091 127 251 AAH08325 128 Resistant cells AF096304 solute carrier family 19 (thiamine transporter), member 2 Hs.30246 128 252 AAD09765 129 Resistant cells AK000948 trichorhinophalangeal syndrome I Hs.26102 129 253 Q9UHF7 130 Resistant cells AI859834 ESTs, Moderately similar to hypothetical protein Hs.445020 130 FLJ20489 131 Resistant cells BF512846 ESTs Hs.442762 131 132 Resistant cells NM_022969 yes fibroblast growth factor receptor 2 (bacteria-expressed Hs.278581 132 254 NP_075258 kinase, keratinocyte growth factor receptor, craniofacial dysostosis 1, Crouzon syndrome, Pfeiffer syndrome, Jackson-Weiss syndrome) 133 Resistant cells AA741493 yes ESTs Hs.143842 133 134 Resistant cells NM_001424 epithelial membrane protein 2 Hs.29191 134 255 P54851 135 Resistant cells AW242920 yes ESTs Hs.129368 135 136 Resistant cells W44413 small protein effector 1 of Cdc42 Hs.22065 136 256 Q9HB17 137 Resistant cells AK021717 Homo sapiens cDNA FLJ11655 fis, clone Hs.287436 137 HEMBA1004554

Table 3 presents a resistance/sensitivity prediction of the 23 breast cell lines for BMS-A in the ‘leave one out’ cross validation test using a Weighted Voting algorithm. The true class is assigned as in Table 1, based on the IC₅₀ results. The predicted class was determined by using the optimal 15 and 7 polynucleotides as the predictor set to predict the resistance or sensitive class. These polynucleotides were selected either from the 137 polynucleotides derived from three analysis methods as shown in Table 2, or from 40 drug treatment modulated polynucleotides as indicated in Table 2. “S” represents Sensitive; “R” represents Resistant. The PS score refers to prediction strength for each prediction made on a cell line by the predictor set. The PS score ranges from 0 to 1, i.e., corresponding from low to high confidence in making the prediction. The error predictions are indicated by an asterisk (*).

TABLE 3 7 modulated markers from 40 15 markers from 137 polynucleotides as indicated in polynucleotides in Table 2 Table 2 Cell Line True Class Predicted Class PS score Error? Predicted Class PS score Error? MDAMB157 S S 0.627 S 0.696 MDAMB231 S S 0.857 S 1.000 HCC1954 S S 0.416 S 0.847 HCC70 S S 0.695 S 1.000 BT20 S S 0.586 S 0.794 HCC1806 S S 0.985 S 1.000 Hs578T S S 0.775 S 0.570 HCC1419 R R 1.000 R 1.000 SkBr3 R R 0.852 R 0.992 AU565 R R 0.629 R 0.763 HCC38 R S 0.101 * S 0.501 * BT474 R R 0.938 R 1.000 MDAMB468 R R 0.392 R 0.416 HCC1428 R R 0.623 R 0.939 MDAMB435S R S 0.723 * R 0.324 H3396 R R 1.000 R 1.000 BT549 R R 0.029 R 0.012 Zr-75-30 R R 0.958 R 1.000 MCF7 R R 0.911 R 1.000 Her2MCF7 R R 0.991 R 1.000 MDAMB436 R R 0.340 R 0.412 Zr-75-1 R R 1.000 R 1.000 MDAMB453 R R 0.983 R 1.000

Table 4 lists the predictor set of 15 polynucleotides used in prediction as shown in Table 3. These 15 polynucleotides were selected from the 137 polynucleotides derived from three analysis methods as shown in Table 2. The relative expression pattern, i.e., sensitive or resistant, polynucleotide description and Unigene cluster number for this 15 predictor polynucleotide subset are indicated in Table 4.

TABLE 4 Highly Modulated Unigene Expressed by Cluster in BMS-A Unigene Title No. Sensitive cells EphB2 Hs.125124 Sensitive cells parvin, alpha Hs.44077 Sensitive cells yes coagulation factor II (thrombin) Hs.154299 receptor-like 1 Sensitive cells yes aldo-keto reductase family 1, Hs.78183 member C3 Sensitive cells yes interferon, gamma-inducible Hs.155530 protein 16 Sensitive cells yes jagged 1 (Alagille syndrome) Hs.91143 Sensitive cells hypothetical protein MGC13105 Hs.22744 Sensitive cells snail homolog 2 (Drosophila) Hs.93005 Resistant cells Homo sapiens mRNA cDNA Hs.4774 DKFZp761C1712 Resistant cells yes Homo sapiens cDNA FLJ31753 Hs.349283 fis, clone NT2RI2007468 Resistant cells ATP-binding cassette, sub- Hs.26630 family A (ABC1), member 3 Resistant cells CGI-81 protein Hs.279583 Resistant cells yes ESTs Hs.445708 Resistant cells EST Hs.159643 Resistant cells hypothetical protein LOC112868 Hs.97837

Table 5 lists the predictor set of 7 polynucleotides used in prediction as shown in Table 3. These 7 polynucleotides were selected from the 40 polynucleotides that were modulated by drug treatment as indicated in Table 2. The relative expression pattern, i.e., sensitive or resistant, polynucleotide description and Unigene cluster number for this 7 predictor polynucleotide subset are indicated in Table 5.

TABLE 5 Highly Modulated Unigene Expressed by Cluster in BMS-A Unigene Title No. Resistant cells yes Homo sapiens cDNA FLJ31753 Hs.349283 fis, clone NT2RI2007468 Sensitive cells yes jagged 1 (Alagille syndrome) Hs.91143 Sensitive cells yes interferon, gamma-inducible Hs.155530 protein 16 Sensitive cells yes coagulation factor II (thrombin) Hs.154299 receptor-like 1 Resistant cells yes ESTs Hs.445708 Sensitive cells yes aldo-keto reductase family 1, Hs.78183 member C3 Sensitive cells yes polymerase I and transcript Hs.29759 release factor

Table 6 lists the representative RT-PCR primer sets for each of the protein tyrosine kinase biomarker polynucleotides of the present invention. The SEQ ID NO: for each RT-PCR primer is provided (SEQ ID NO:257 thru 530).

TABLE 6 Genbank Accession No. RT-PCR Primer Type Rt-PCR Primer Sequence SEQ ID NO: NM_004431 Forward Primer TCCTCACACTAAGAGGGCAGA 257 NM_004431 Reverse Primer ACCTCAACACAACCAAGCATC 258 AF025304 Forward Primer TCAGTGAGTACAACGCCACAG 259 AF025304 Reverse Primer CTTCTCCTGGATGCTTGTCTG 260 NM_001753 Forward Primer CCACCTTCACTGTGACGAAAT 261 NM_001753 Reverse Primer CCAGATGTGCAGGAAAGAGAG 262 NM_001233 Forward Primer AGCTGTCTGCACATCTGGATT 263 NM_001233 Reverse Primer CCTGGGGTCCAAGTATTCAAT 264 NM_000700 Forward Primer CATCAAGCCATGAAAGGTGTT 265 NM_000700 Reverse Primer ACAAAGAGCCACCAGGATTTT 266 NM_004039 Forward Primer GAACTGATGTTCCCAAGTGGA 267 NM_004039 Reverse Primer AACCAGGTTCAGGAAAGCATT 268 BG107577 Forward Primer TTTCGTGAACAAGCACCTGA 269 BG107577 Reverse Primer ATGAGCTCAAAGGCAAAGGA 270 BE965369 Forward Primer GTTTAAAATCCGGATTGGCAT 271 BE965369 Reverse Primer GTGGCCGTGATAATTTTTGAA 272 NM_001993 Forward Primer AAAATGGAAGGAAATTGGGTG 273 NM_001993 Reverse Primer TGCCCAGAATACCAATGTCTC 274 BF792126 Forward Primer TCGGTGAATTCAAGGACCAT 275 BF792126 Reverse Primer GCTGCCTTCAAGGATCTCAC 276 E856341 Forward Primer TGCCAGGTAAAGCTCTGTCC 277 E856341 Reverse Primer GTCCTGTGGATGAGCATGTG 278 U17496 Forward Primer ATCTCCAGAGCTCGCTTTACC 279 U17496 Reverse Primer TTCACCCGTAAGGCACTAATG 280 NM_002800 Forward Primer TATGGTTATGTGGATGCAGCA 281 NM_002800 Reverse Primer AGATGACTCGATGGTCCACAC 282 NM_000311 Forward Primer CCGAGTAAGCCAAAAACCAA 283 NM_000311 Reverse Primer CTCATCCATGGGCCTGTAGT 284 NM_003739 Forward Primer GGTGAGGAACTTTCACCAACA 285 NM_003739 Reverse Primer CTTGAGTCCTGGCTTGTTGAG 286 NM_020639 Forward Primer TACTTGGGTGAGTCCTTGTGG 287 NM_020639 Reverse Primer GACTCTTAGGCCTGTGGCTCT 288 AF208043 Forward Primer GGAGTAAGGTGTCCGAGGAAC 289 AF208043 Reverse Primer CTGACATTTGGCCACTGTTTT 290 AF003837 Forward Primer CCTGTAACATAGCCCGAAACA 291 AF003837 Reverse Primer AGTTGTCTCCATCCACACAGG 292 BC002832 Forward Primer ACGTGTATGCAGATGGAAAGG 293 BC002832 Reverse Primer CAGAGGCTGTGACGTTGTGTA 294 NM_006994 Forward Primer AATTTGTGCAGTTGGGAGATG 295 NM_006994 Reverse Primer TGATCTCTACCCTGCAGCTGT 296 AF327443 Forward Primer CATCTGACTTCACCTGTGGGT 297 AF327443 Reverse Primer TTCTGACTGTCCCTGCTGACT 298 NM_021615 Forward Primer ACCCCGACGTCTTCTACCTAA 299 NM_021615 Reverse Primer GCAGATAGGCATCAAACACGT 300 AF104857 Forward Primer AGTTCCCTGGGCATAATGAGT 301 AF104857 Reverse Primer AACATGAGAGCTTGGGATCCT 302 AL136896 Forward Primer AGCCGAATCCACTCTCATGT 303 AL136896 Reverse Primer TAACAAGGCACAGCAAGCAG 304 AL565621 Forward Primer CTCAGACCTTTGCCCTTCTCT 305 AL565621 Reverse Primer TCCGGCTCAGACTGAATAAGA 306 BF111719 Forward Primer CACACATGGGCATTTGCTTA 307 BF111719 Reverse Primer GGATATGCAGTGGGAAGGAA 308 BC020608 Forward Primer CACCGAGAATCCTTACACCAA 309 BC020608 Reverse Primer CAGAATCCATCCTCCTTCCTC 310 AW575374 Forward Primer CATGCACACACACACAGAATG 311 AW575374 Reverse Primer TTTCCTTTGGAAACTGGGATT 312 NM_001401 Forward Primer CTTGCTGAATTCAACTCTGCC 313 NM_001401 Reverse Primer AAACCACAGAGTGGTCATTGC 314 BC001247 Forward Primer AGGAGAAGGAAGACAAGCCAG 315 BC001247 Reverse Primer CTTGCTGATTTCGTCTTCAGG 316 BE669858 Forward Primer CTGCTTGAGACTGTTCTGGGT 317 BE669858 Reverse Primer GATTAGAGGGCTTCCTCATGG 318 NM_000127 Forward Primer CAAGGGGAAGAGGTACCTGAC 319 NM_000127 Reverse Primer TCTGTCACAGCGAGAATCCTT 320 NM_002589 Forward Primer GACTCTGGGCGTCTCTGAAG 321 NM_002589 Reverse Primer CAGCAACAAGCCAGTCTCAA 322 AI133452 Forward Primer ACATCATGAGTTGGTCCTTGC 323 AI133452 Reverse Primer AATCTGCAATGCCACAGGTAG 324 NM_006101 Forward Primer TCCTCATACATGGCCTCACA 325 NM_006101 Reverse Primer TGTCGGCACCACTCATAAAA 326 AL135264 Forward Primer GGTGCAGGTTGACACTGAAA 327 AL135264 Reverse Primer AAGGTTCACCAGGACACAGG 328 NM_014164 Forward Primer ATCACAGGCATCATCATCCTC 329 NM_014164 Reverse Primer GGTTGTCAGCTCCTGTTTCTG 330 BC003502 Forward Primer GGGGTGTAGGTGGGAGTCAC 331 BC003502 Reverse Primer AGTGCCTTCAGCCAAAATGT 332 AA780067 Forward Primer GCCATCCTCTTGATAAGCTGA 333 AA780067 Reverse Primer TCTTCCCAGGATTCTCTTTGG 334 AA702248 Forward Primer GATTGCAGATCCTATGCAGGA 335 AA702248 Reverse Primer GCATCCAGGACAACACAAAGT 336 BC004372 Forward Primer AAGGTGGAGCAAACACAACC 337 BC004372 Reverse Primer TCCACTTGGCTTTCTGTCCT 338 BF688144 Forward Primer CAAGTGCCCATTTAGGTTTGA 339 BF688144 Reverse Primer ACTGACAGATGGCTCATTTGG 340 NM_018067 Forward Primer GAACACCAGAGACACTCCTGC 341 NM_018067 Reverse Primer ACATCCTGGTAGGTGATGCAG 342 BG111761 Forward Primer CGCATCTGTCCAGCATCTTA 343 BG111761 Reverse Primer CAAAACCGGGACGCTAACT 344 NM_017821 Forward Primer AGAAACAGTGGATCACGTTGG 345 NM_017821 Reverse Primer TTCCAAGGGAATACCCAAAAC 346 AA722799 Forward Primer GTTTCCACTTTTCCCAGTGC 347 AA722799 Reverse Primer TCACATGAAACGATTCTCTGCT 348 BC006436 Forward Primer AATGTCAAAAGTGTGGGCAAG 349 BC006436 Reverse Primer ATGTGGACCGAGTAAAGGCTT 350 NM_006548 Forward Primer CAGTCCCGGGTAGATATCCAT 351 NM_006548 Reverse Primer TCTTCGGCTAGTTTGGTCTCA 352 NM_002194 Forward Primer TGATTTGCCACAGTTGGTGTA 353 NM_002194 Reverse Primer CTAGGTATGCGTCTCTGCAGG 354 BG251556 Forward Primer CAGCCTGGTTTACAAATTCCA 355 BG251556 Reverse Primer TGGGGAAAACTAAGGCAAAGT 356 J03202 Forward Primer CAACAATGAAGGCTGCTCTTC 357 J03202 Reverse Primer CCTGCTTCAGTGAGAGAATGG 358 NM_000245 Forward Primer AGGACCGGTTCATCAACTTCT 359 NM_000245 Reverse Primer TCAATGTAGGACTGGTCCGTC 360 NM_002444 Forward Primer AAATGGTGCCTTCAAGACCTT 361 NM_002444 Reverse Primer CCGGCCTATACTCCTACAAGG 362 NM_012334 Forward Primer TAATGGTGGTCTGAACAAGGC 363 NM_012334 Reverse Primer AGTTGGCCCAAGTCCTTAAAA 364 A1769569 Forward Primer CATGGAGGAGCCATACAACA 365 A1769569 Reverse Primer TTTGTCCTGCTCCCAAATTC 366 NM_002633 Forward Primer TGCTTTGTATGAGACCCCAAC 367 NM_002633 Reverse Primer CATCTTTCTCACGGATGTGGT 368 BC004295 Forward Primer AGAAGACAGAGAGGTCAGCCC 369 BC004295 Reverse Primer TGGGACCCTAATTTTCTGGAC 370 NM_016205 Forward Primer ACCCTTGAGTTTTCGCCTCT 371 NM_016205 Reverse Primer GGATGAAAGCAAAACCTGGA 372 NM_004815 Forward Primer GCCCCTTTTGTATAGGACTGC 373 NM_004815 Reverse Primer AATTCCAGTGAGGCACAAATG 374 NM_002872 Forward Primer CAAGACCTGCCTTCTCATCAG 375 NM_002872 Reverse Primer GAAGACGTCCGTCTGTGGATA 376 AF329267 Forward Primer CAATTCTCTCAGCAGACCTGG 377 AF329267 Reverse Primer ACCACGGAGTCAAAACCTTCT 378 AI572079 Forward Primer CCCCAAGGCACATACTGTTAA 379 AI572079 Reverse Primer TGCCCATTGTTGAACTAAAGC 380 NM_001549 Forward Primer GAACATGCTGACCAAGCAGA 381 NM_001549 Reverse Primer CAGTTGTGTCCACCCTTCCT 382 D50683 Forward Primer AACAATACTGGCTGATCACCG 383 D50683 Reverse Primer CATGGAGTGTGATCACTGTGG 384 NM_005902 Forward Primer GGACTGCAGTGTGGAGTTCA 385 NM_005902 Reverse Primer GAGAGGGGAGGGAGACAGAC 386 NM_014452 Forward Primer GGTTTATAAGCCTTTGCCAGG 387 NM_014452 Reverse Primer GTGGGAAAAGTCACACTGCAT 388 AB017644 Forward Primer CTCCTCCTAATTGCAGTGCTG 389 AB017644 Reverse Primer GTGATAGATTCTGGTGCGGAA 390 BC002323 Forward Primer CCTCAGGTCCAACTCCATGT 391 BC002323 Reverse Primer GTGCCCCAATTTTTGATTTG 392 AL157452 Forward Primer AGCCTTGTCTCCCTTGGATT 393 AL157452 Reverse Primer TCAGTTGCCCCTCTACAACC 394 BF752277 Forward Primer AAGGCCCTGGATTCTCACTC 395 BF752277 Reverse Primer GCCAGGACACCTTCAGAGAG 396 BF512299 Forward Primer AAGAGCCTCCCAAAGGAAA 397 BF512299 Reverse Primer GGGAAATGAAAGTGGCAAGA 398 AL049381 Forward Primer TTGTTGGTTTTATTCTCCCCC 399 AL049381 Reverse Primer CAGTTGGAATCAAAAGGGACA 400 NM_002585 Forward Primer AGTGAGGAAGCCAAAGAGGAG 401 NM_002585 Reverse Primer TTTGGCAGCATAAATATTGGC 402 T68445 Forward Primer CAGAGAGGGAACCACCAGAG 403 T68445 Reverse Primer CCCTGGGGAAATTAAAATGA 404 BF308645 Forward Primer CTCTGTCGGGAAAGGAGAGA 405 BF308645 Reverse Primer GAACTTTGACGACACCGACA 406 AF088867 Forward Primer CTCTGGCCAGAGATACCACAG 407 AF088867 Reverse Primer CATCAAGGGTTTGTTGCTTGT 408 NM_004040 Forward Primer AACTATGTGGCCGACATTGAG 409 NM_004040 Reverse Primer CACCGAGAAGCACATGAGAAT 410 AF151810 Forward Primer CCTGAAGAACCGTGATGTCAT 411 AF151810 Reverse Primer CTGTGCTCTGGATGAGGTAGC 412 NM_004252 Forward Primer CACATCCCCTTTCTTGACAAA 413 NM_004252 Reverse Primer GATGAGGCACTCAGTGAGGAG 414 NM_005749 Forward Primer TTGAAACCTAATTTTGTGGCG 415 NM_005749 Reverse Primer AAATGTTGACACGTCTCCTGG 416 NM_003225 Forward Primer CCTAATACCATCGACGTCCCT 417 NM_003225 Reverse Primer AGCTCTGGGACTAATCACCGT 418 AA181060 Forward Primer AAAAGGCTGACAAACTGACCA 419 AA181060 Reverse Primer TCACAGCCTAGGTAAGAGCCA 420 AL050025 Forward Primer CAGGTACGAATTTTGCGGTTA 421 AL050025 Reverse Primer TCGCAATCCACTCTCTGACTT 422 NM_001089 Forward Primer CTCCTTCAGCTTCATGGTCAG 423 NM_001089 Reverse Primer TCTGGCTCAGAGTCATCCAGT 424 NM_004915 Forward Primer CAACCCAGCAGATTTTGTCAT 425 NM_004915 Reverse Primer CGAGGTCTCTCTTGTGGTCTG 426 AL523275 Forward Primer TCTTTGCATTGAGATTGGTCC 427 AL523275 Reverse Primer ACCGTGAAAAATGCACATCTC 428 NM_001218 Forward Primer CCTTCAATCCGTCCTATGACA 429 NM_001218 Reverse Primer GGAAGCAGCTCTTCAATGTTG 430 NM_016286 Forward Primer GAGTGAATGCAGTAAACCCCA 431 NM_016286 Reverse Primer CACTCAGCAGAAAGAGGATGG 432 BC000185 Forward Primer CATCGAGGACGCTACTTCAAG 433 BC000185 Reverse Primer AAAATAGGCCTGACGACACCT 434 NM_005505 Forward Primer TTGGACAAACTGGGAAGATTG 435 NM_005505 Reverse Primer ACGTACTGGGCATAGTGCATC 436 NM_016048 Forward Primer GGGGATATTATTAGCGTGGGA 437 NM_016048 Reverse Primer TGCCGCTTCTACTTCTGGTAA 438 BC000195 Forward Primer TCCACTCACATTTCCTATCGG 439 BC000195 Reverse Primer GATTCCATTTACGGGGAAAAA 440 NM_001306 Forward Primer AACCTGCATGGACTGTGAAAC 441 NM_001306 Reverse Primer AATATCAAGTGCCCCTTCCAG 442 BC000021 Forward Primer GCAAGTATAGCGCATTTGAGC 443 BC000021 Reverse Primer CGTCTTGAAGTCCATGGAGAG 444 W68084 Forward Primer TTAGATCTGAAGCCCTGGGTT 445 W68084 Reverse Primer TGCTTGGTGAACATAACACCA 446 AA825563 Forward Primer AGAAGAAAAACCCAAATGGCA 447 AA825563 Reverse Primer TCCATAGTGGTTTTTACCAGCA 448 BE887449 Forward Primer TGCGTACCAGGATTGGTTAAG 449 BE887449 Reverse Primer GATGTCCAACAAAACGCTCAT 450 AI123815 Forward Primer TGAGCATGGTATACTTTTGGG 451 AI123815 Reverse Primer AAGCTTATAGGAATGGGCCAG 452 AI308862 Forward Primer TGGGAAAATTTAAAACCCACA 453 AI308862 Reverse Primer TCAAAGTGCCCTTTGGTAGTG 454 AW006352 Forward Primer TCCTCAAACACAAAATCCCAG 455 AW006352 Reverse Primer CTCCTACTATGGGCCTCCAAC 456 AL554277 Forward Primer GAAGCAGATCGTCCTGAACTG 457 AL554277 Reverse Primer GCTCATCATCCTCTTCTCCCT 458 BG289001 Forward Primer TCCCAATAGCTTGTGGATCAG 459 BG289001 Reverse Primer ATCAACCAGGAAGCCAACTTT 460 AI935915 Forward Primer GACCAACACCTCTCCTAAGGG 461 AI935915 Reverse Primer GTTGGGAGGGGACCATAGTTA 462 NM_017689 Forward Primer GAAATAGCAAAAACAAGGCCC 463 NM_017689 Reverse Primer CAATGCAGCACATGCTAGAAA 464 NM_017966 Forward Primer CAGAATGTAAAGGGTGGGGAT 465 NM_017966 Reverse Primer CCCTGAGACCTGGTTTACCTC 466 AI923458 Forward Primer GATGGCAGCTATGAAGTCCTG 467 AI923458 Reverse Primer GCATTCCAGCTATCACCTGAA 468 NM_000597 Forward Primer CACCTCTACTCCCTGCACATC 469 NM_000597 Reverse Primer AGAAGAGATGACACTCGGGGT 470 U90304 Forward Primer TTTGGCTAAAGACCCGAAAAT 471 U90304 Reverse Primer TCTCTCTCTCTCGGTGATGGA 472 NM_004968 Forward Primer GAGCAGGAAAGATGATGCAAG 473 NM_004968 Reverse Primer AAGTATCTGAGATGGCCCGAT 474 AL563283 Forward Primer CTCTGGAATGGACTGAAGCTG 475 AL563283 Reverse Primer AAAAGTCCAGGAGCTGGAGAG 476 AA135522 Forward Primer CACCTCATCACAACACCCTCT 477 AA135522 Reverse Primer TGCTAGGATCCACCCTCCTAT 478 AI867102 Forward Primer CTCTTCCCAGCTCCTGATTCT 479 AI867102 Reverse Primer CTGAAGGACTGAAGGGAGCTT 480 AW134976 Forward Primer ACATGCTGTGTGGTAGAGGCT 481 AW134976 Reverse Primer AACATGCATGCATTGTACCAA 482 AW665865 Forward Primer TTCCAGGAAGAACATCATTGC 483 AW665865 Reverse Primer CTTTTCCTTCAGGGAACCAAG 484 AB051487 Forward Primer TTCTCAGCCAAAGCAGATGTT 485 AB051487 Reverse Primer TGCTTCTCCTCAGCAATTTGT 486 AB050049 Forward Primer ACTATGGGATGTGTGGCAGAG 487 AB050049 Reverse Primer GCTCTTTTAAAGCCGCTTCAT 488 NM_016835 Forward Primer AAAGAGGCTGACCTTCCAGAG 489 NM_016835 Reverse Primer AAGGCAAGGCCTATTTTTCAA 490 AK002075 Forward Primer GAAGCAATGAATAGCATGGGA 491 AK002075 Reverse Primer CCATTCCTCCAGTCACACTGT 492 NM_000933 Forward Primer TCGGTCTTGGCTACTTGAAGA 493 NM_000933 Reverse Primer CAGCGTTCCAGAAAATCTGAG 494 NM_012391 Forward Primer AAGGAGTTGCTACTCAAGCCC 495 NM_012391 Reverse Primer CTTGTAATACTGGCGGATGGA 496 NM_006443 Forward Primer CCATCCTTGGGTGTAGGCTAT 497 NM_006443 Reverse Primer CTCGAAGTATCGATCCAGCAG 498 BC015948 Forward Primer ATGTGCCCTCACATCTGTTTC 499 BC015948 Reverse Primer GGGTTTTAACAGCAGGGTAGC 500 AF153330 Forward Primer GAAATCAGTCTACCAAGGGGC 501 AF153330 Reverse Primer CGACTTTGCAATCTTGACACA 502 BC002702 Forward Primer GAAGAGTGGGCAAACATGAAA 503 BC002702 Reverse Primer CCCACCTGGGAGTAAGTCTTC 504 NM_006416 Forward Primer CCAGGTGACCTACCAGTTGAA 505 NM_006416 Reverse Primer TTCCACCACCACTTTTGTAGC 506 NM_030674 Forward Primer TGGCAAACAGTGGAATCCTAC 507 NM_030674 Reverse Primer TCTGTAGAGAGGTGGCTCCAA 508 AF212371 Forward Primer CGGATGCTCAGCATCTTCTAC 509 AF212371 Reverse Primer ACTACCAGGAACAGCAGCAGA 510 AF096304 Forward Primer AGGCAATCCGATTTACGACTT 511 AF096304 Reverse Primer CTCTGCCTCCTTCATCAACAG 512 AK000948 Forward Primer AGAAGGACTTCTCCAGCAAGG 513 AK000948 Reverse Primer CTGGGACAGAATGGACAGTGT 514 AI859834 Forward Primer TGGCCATTCAGACAGCATTA 515 AI859834 Reverse Primer CAGCTACTTGGGAGGCTGAG 516 BF512846 Forward Primer GGGCCCACTTGACTCATTTA 517 BF512846 Reverse Primer GCCTGCAGAGATCTCACTTTG 518 NM_022969 Forward Primer ACAGGATGGGCCTCTCTATGT 519 NM_022969 Reverse Primer TCCTCAGGAACACGGTTAATG 520 AA741493 Forward Primer ACACCTTGGTACCACCAATCA 521 AA741493 Reverse Primer GGTCTCTTGCCTTCATCCAGT 522 NM_001424 Forward Primer GCATCGCCTTCTTCATCTTC 523 NM_001424 Reverse Primer CGTAGCTGCCTTCTCTGGTC 524 AW242920 Forward Primer TTCATGCGTGAAAGTGTGAAG 525 AW242920 Reverse Primer TTTGATCAAAGGGTGTCATCAG 526 W44413 Forward Primer GGTAGGGAGCTTCTCAGCAA 527 W44413 Reverse Primer GTTAGCCCAGAGGAGCTCAA 528 AK021717 Forward Primer CACAGAAAACACCCCCACTT 529 AK021717 Reverse Primer ACTGTATGGAGGCCCAGTTG 530

Table 7 presents a resistance/sensitivity prediction of the 12 additional breast cancer cell lines for a protein tyrosine kinase inhibitor compound BMS-A by using the 137 polynucleotides (listed in Table 2), 40 polynucleotides whose expression were modulated by the drug treatment (indicated in Table 2), 15 polynucleotides (Table 4) and 7 polynucleotides (Table 5) as the predictor sets that were previously identified from the 23 breast cancer cell lines. The resistance/sensitivity phenotype classification of the 12 additional breast cancer cell lines for BMS-A is based on IC₅₀ results. The IC₅₀ for each cell line was assessed in by MTS assays as described in Example 1 (Methods). The IC₅₀ unit is μM. The cell lines with a IC₅₀ below 1 μM were defined as sensitive to the compound, while those having a IC₅₀ above 1 μM were considered to be resistant. “S” represents Sensitive; “R” represents Resistant. The GeneCluster software was used to build different predictor sets using the above mentioned different polynucleotides, and make sensitivity prediction to BMS-A compound on the 12 additional breast cell lines using a “weighted-voting algorithm”, as described herein. The PS score refers to prediction strength for each prediction made on a cell line by the predictor set. The PS score ranges from 0 to 1, i.e., corresponding from low to high confidence in making the prediction. The error predictions are indicated by an asterisk (*).

TABLE 7 Classi- 137 40 modulated markers 15 markers from 7 modulated markers from IC50 fication polynucleotides in from 137 polynucleotides 137 polynucleotides 40 polynucleotides as (μM) based Table 2 in Table 2 in Table 2 indicated in Table 2 Testing Cell to on Predicted PS Predicated PS Predicted PS Predicted PS Line BMS-A IC50 Class score Error? Class score Error? Class score Error? Class score Error? HCC 1143 0.02346 S S 0.678 S 0.693 S 0.442 S 0.534 MBA-MB- 0.03935 S R 0.710 * R 0.767 * R 0.489 * R 0.653 * 415 HCC 1937 0.07057 S S 0.638 S 0.791 S 0.388 S 0.263 HCC 1395 0.08180 S S 0.209 S 0.052 R 0.236 * R 0.101 * UACC-812 1.21577 R R 0.619 R 0.749 R 0.740 R 0.762 MDA-MB- 1.43833 R R 0.895 R 0.802 R 0.935 R 0.855 361 HCC 1187 1.57932 R S 0.003 * R 0.113 R 0.401 R 0.827 DU 4475 2.63288 R R 0.192 R 0.088 R 0.407 R 0.361 HCC 2157 5.45299 R R 0.183 R 0.202 R 0.453 R 0.352 HCC 202 5.58407 R R 0.506 R 0.853 R 0.263 R 0.478 HCC 2218 8.65145 R R 0.881 R 0.898 R 0.629 R 0.515 HCC 1500 >8.92618 R R 0.783 R 0.786 R 0.627 R 0.890

Table 8 lists the predictor set of 6 polynucleotides that were used in prediction as shown in Tables 9-12. The relative expression pattern, i.e., sensitive or resistant in the original 23 breast cancer cell lines, gene description and Unigene cluster number for this 6 predictor subset are indicated.

TABLE 8 Highly Unigene Expressed in Unigene Title Cluster No. Sensitive cells EphA2 Hs.171596 Sensitive cells caveolin 1, caveolae protein, 22 kD Hs.74034 Sensitive cells caveolin 2 Hs.139851 Resistant cells annexin A2 Hs.406239 Sensitive cells polymerase I and transcript release factor Hs.29759 Resistant cells insulin-like growth factor binding protein Hs.433326 2 (36 kD)

Table 9 presents a resistance/sensitivity prediction of the 12 additional breast cancer cell lines for the protein tyrosine kinase inhibitor compound BMS-A by using the selected 6 polynucleotides as the predictor set (shown in Table 8) that were previously identified from 23 breast cell lines. The resistance/sensitivity phenotype classification of the 12 additional breast cell lines for BMS-A is based on IC₅₀ results and is defined in Table 7. The prediction was conducted the same way as in Table 7. “S” represents Sensitive; “R” represents Resistant. The PS score refers to prediction strength for each prediction made on a cell line by the predictor set. The PS score ranges from 0 to 1, i.e., corresponding from low to high confidence in making the prediction. The error predictions are indicated by an asterisk (*).

TABLE 9 Classification 6 markers as indicated in Table 8 Testing Cell Line based on IC50 Predicted Class PS score Error? HCC 1143 S S 1 MBA-MB-415 S R 0.928 * HCC 1937 S S 1 HCC 1395 S S 0.507 UACC-812 R R 1 MDA-MB-361 R R 1 HCC 1187 R R 0.713 DU 4475 R R 0.432 HCC 2157 R R 0.177 HCC 202 R R 0.723 HCC 2218 R R 1 HCC 1500 R R 1

Table 10 shows the error rate for predicting the sensitivity classification of the additional 12 breast cell lines to compound BMS-A using the 6 polynucleotides as the predictor set (shown in Table 8). 1 out of 12 cell lines predicted incorrectly, resulting a normalized error rate of 12.5%.

TABLE 10 # of # of # Correct Errors in % Correct % Error in Per Class prediction prediction prediction prediction Sensitive 4 3 1 75%   25% Resistant 8 8 0 100%   0% Total 12 11 1 Normalized 12.5% Error Rate

Table 11 presents a resistance/sensitivity prediction of the 23 lung cancer cell lines for the protein tyrosine kinase inhibitor compound BMS-A by using the 6 polynucleotides identified from breast cell lines as the predictor set (shown in Table 8). The resistance/sensitivity phenotype classification of the 23 lung cancer cell lines for BMS-A is based on IC₅₀ results. The IC₅₀ for each cell line was assessed by MTS assays as described in Example 1 (Methods). The mean IC₅₀ values along with standard deviations (SD) were calculated from 2 to 5 individual determinations for each cell line as shown. The IC₅₀ unit is μM. The cell lines with a IC₅₀ below 1 μM were defined as sensitive to the compound, while those having a IC₅₀ above 1 μM were considered to be resistant. “S” represents Sensitive; “R” represents Resistant. The GeneCluster software was utilized to build a predictor set using the 6 selected polynucleotides listed in Table 8 and make sensitivity prediction on the 23 lung cancer cell lines. The PS score refers to prediction strength for each prediction made on a cell line by the predictor set. The PS score ranges from 0 to 1, i.e., corresponding from low to high confidence in making the prediction. The error predictions are indicated by an asterisk (*).

TABLE 11 # of Mean IC₅₀ Classification Pre- MTS (μM) to based on dicted PS Cell Line Tests BMS-A Mean IC₅₀ Class score Error Sk-LU-1 4 0.01375 S S 1.00 L2987 4 0.03711 S S 0.62 H226 3 0.05825 S S 0.62 H838 4 0.07240 S S 0.21 H661 4 0.12313 S S 0.07 NCI-H596 2 0.12379 S S 0.08 H441 4 0.14109 S S 0.40 SK-MES-1 3 0.15119 S S 1.00 H522 3 0.21506 S R 0.96 * SW1271 2 0.24237 S S 0.88 SW900 3 0.50737 S S 0.89 H2347 3 1.02459 R R 1.00 ChaGo-K-1 4 >1.025 R S 0.60 * A549 5 >1.025 R S 0.58 * H1155 5 1.02459 R R 0.93 H23 5 1.02459 R S 0.77 * A-427 4 >1.025 R R 0.77 Calu-6 3 >1.025 R R 0.67 DMS114 5 >1.025 R R 1.00 DMS53 4 >1.025 R R 1.00 H157 4 >1.025 R R 0.36 LX-1 4 >1.025 R R 1.00 SHP-77 5 >1.025 R R 1.00

Table 12 shows the error rate for predicting the sensitivity classification of the 23 lung cancer cell lines to compound BMS-A using the 6 polynucleotides as the predictor set (shown in Table 7). 4 out of 23 cell lines predicted incorrectly, resulting a normalized error rate of 17%.

TABLE 12 # of Errors # Per # of Correct in % Correct % Error in Class prediction prediction prediction prediction Sensitive 11 10 1 91% 9% Resistant 12 9 3 75% 25% Total 23 19 4 Normalized 17% Error Rate

Table 13. shows p-value in t-test when comparing the expression level of selected 4 markers between sensitive and resistant breast cell lines as defined in Table 1 for the data from both Affymetrix Genechip and quantitative RT-PCR.

TABLE 13 p-value in t-test EphA2 EphB2 Caveolin-1 Caveolin-2 Affychip 0.0061 0.0001 0.0027 0.0004 RT-PCR 0.0472 0.0021 0.0738 0.0251

DETAILED DESCRIPTION OF THE INVENTION

The present invention describes the identification of polynucleotides that correlate with drug sensitivity or resistance of untreated cell lines to determine or predict sensitivity of the cells to a drug, compound, or biological agent. These polynucleotides, called marker or predictor polynucleotides herein, can be employed for predicting drug response. The marker polynucleotides have been determined in an in vitro assay employing microarray technology to monitor simultaneously the expression pattern of thousands of discrete polynucleotides in untreated cells, whose sensitivity to compounds or drugs, in particular, compounds that modulate, e.g., inhibit, protein tyrosine kinase or protein tyrosine kinase activity is tested. The protein tyrosine kinases, or activities thereof, associated with response to a drug, compound, or biological agent include, for example, members of the Src family of protein tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as the Bcr-abl, Jak, PDGFR, c-kit and Eph receptors protein tyrosine kinases. (See, e.g., P. Blume-Jensen and T. Hunter, 2001, “Oncopolynucleotide Kinase Signaling”, Nature, 411:355-365).

The assay according to this invention has allowed the identification of the marker polynucleotides, called protein tyrosine kinase biomarkers herein, having expression levels in the cells that are highly correlated with drug sensitivity exhibited by the cells. Such marker polynucleotides encompass the above-listed protein tyrosine kinase-encoding polynucleotides, and serve as useful molecular tools for predicting a response to drugs, compounds, biological agents, chemotherapeutic agents, and the like, preferably those drugs and compounds, and the like, that affect protein tyrosine kinase activity via direct or indirect inhibition or antagonism of the protein tyrosine kinase function or activity.

In its preferred aspect, the present invention describes polynucleotides that correlate with sensitivity or resistance of breast cell lines to treatment with a protein tyrosine kinase inhibitor compound, e.g., BMS-A, as described herein. (FIG. 1 and Table 2). The protein tyrosine kinase inhibitor compound, BMS-A, utilized for identifying the polynucleotide predictor sets of this invention, was described in WO 00/62778, published Oct. 26, 2000, and is hereby incorporated by reference in its entirety. BMS-A has potent inhibitory activity for a number of protein tyrosine kinases, for example, members of the Src family of protein tyrosine kinases, including Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as the Bcr-abl, Jak, PDGFR, c-kit and Eph receptors protein tyrosine kinases. Specifically, for the BMS-A protein tyrosine kinase inhibitor compound analyzed, the expression of 137 predictor polynucleotides was found to correlate with resistance/sensitivity of the breast cell lines to the compound.

In accordance with the invention, an approach has been discovered in which polynucleotides and combinations of polynucleotides have been identified whose expression pattern, in a subset of cell lines, correlates to and can be used as an in vitro predictor of cellular response to treatment or therapy with one compound, or with a combination or series of compounds, that are known to inhibit or activate the function of a protein, enzyme, or molecule (e.g., a receptor) that is directly or indirectly involved in cell proliferation, cell responses to external stimuli, (such as ligand binding), or signal transduction, e.g., a protein tyrosine kinase. Preferred are antagonists or inhibitors of the function of a given protein, e.g., a tyrosine kinase.

In a preferred aspect, the BMS-A protein tyrosine kinase inhibitor was employed to determine drug sensitivity in a panel of breast cell lines following exposure of the cells to this compound. Some of the cell lines were determined to be resistant to treatment with the inhibitor compound, while others were determined to be sensitive to the inhibitor. (Table 1). A subset of the cell lines examined provided an expression pattern or profile of polynucleotides, and combinations of polynucleotides, that correlated to, and thus serve as a predictor of, a response by the cells to the inhibitor compound, and to compounds having similar modes of action and/or structure. (FIG. 1 and Tables 2, 4-5, and 8).

Such a predictor set of cellular polynucleotide expression patterns correlating with sensitivity or resistance of cells following exposure of the cells to a drug, or a combination of drugs, provides a useful tool for screening a cancer, tumor, or patient test sample before treatment with the drug or a drug combination. The screening technique allows a prediction of cells of a cancer, tumor, or test sample exposed to a drug, or a combination of drugs, based on the polynucleotide expression results of the predictor set, as to whether or not the cancer, tumor, or test sample, and hence a patient harboring the cancer and/or tumor, will or will not respond to treatment with the drug or drug combination. In addition, the predictor polynucleotides or predictor polynucleotide set can also be utilized as described herein for monitoring the progress of disease treatment or therapy in those patients undergoing treatment involving a protein tyrosine kinase, e.g., src tyrosine kinase, inhibitor compound or chemotherapeutic agent for a disease, e.g., breast cancer.

According to a particular embodiment of the present invention, oligonucleotide microarrays were utilized to measure the expression levels of over 44,792 probe sets in a panel of 23 untreated breast cell lines for which the drug sensitivity to the protein tyrosine kinase inhibitor compound was determined. This analysis was performed to determine whether the polynucleotide expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Data analysis allowed the identification of marker polynucleotides whose expression levels were found to be highly correlated with drug sensitivity. In addition, the treatment of cells with the BMS-A protein tyrosine kinase inhibitor compound also provided polynucleotide expression signatures predictive of sensitivity to the compound. Thus, in one of its embodiments, the present invention provides these polynucleotides, i.e., polynucleotide “markers” or “biomarkers” or “predictors”, which show utility in predicting drug response upon treatment or exposure of cells to a drug. In particular, the marker or predictor polynucleotides are protein tyrosine kinase biomarkerspolynucleotides encoding protein tyrosine kinase biomarker proteins/polypeptides, such as a src tyrosine kinase inhibitor biomarker.

The performance of the polynucleotide expression and marker polynucleotide identification analyses embraced by the present invention is described in further detail and without limitation herein below.

IC₅₀ Determination and Phenotype Classification Based on Sensitivity of Twenty-Three Breast Cell Lines to Src Tyrosine Kinase Inhibitor Compounds

Twenty-three breast cell lines were treated with a protein tyrosine kinase inhibitor compound (i.e., BMS-A) to determine the individual IC₅₀ value. The average IC₅₀ values, along with standard deviations, were calculated from 2 to 5 individual determinations for each cell line. As shown in Table 1, a large variation in the IC₅₀ values (>1000-fold) was observed for the compound among the twenty-three breast cell lines.

The IC₅₀ value for each cell line was log₁₀ transformed. The mean of log₁₀(IC₅₀) across the twenty-three breast cell lines was calculated for the compound. The log₁₀(IC₅₀) for each cell line was normalized to the mean of log₁₀(IC₅₀) across the twenty-three breast cell lines for the compound. The cell lines with a log₁₀(IC₅₀) below the mean of log₁₀(IC₅₀) were classified as sensitive to the compound, and those with a log₁₀(IC₅₀) above the mean of log₁₀(IC₅₀) were classified as resistant. Table 1 presents the resistance/sensitivity classifications of the twenty-three breast cell lines to the BMS-A compound. As observed in Table 1, seven cell lines were classified as sensitive and sixteen cell lines were classified as resistant to the protein tyrosine kinase inhibitor compound.

Identifying Polynucleotides that Significantly Correlated with Drug Resistance/Sensitivity Classification

Expression profiling data of 44,792 probe sets represented on the HG-U133 array set for twenty-three untreated breast cell lines were obtained and preprocessed as described in Example 1, Methods. The preprocessed data containing 5322 polynucleotides were analyzed using K-mean Nearest Neighborhood (KNN) algorithm and “signal to noise model” (T. R. Golub et al., 1999, Science, 286:531-537) to identify polynucleotides whose expression patterns were strongly correlated with the drug resistance/sensitivity classification (Table 1). An “idealized expression pattern” corresponds to a polynucleotide that is uniformly high in one class (e.g., sensitive) and uniformly low in the other class (e.g., resistant). Initially, a KNN analysis was performed in which a correlation coefficient was obtained for each polynucleotide using “signal to noise model”. The correlation coefficient, which is a measure of relative classification separation, is obtained using the following formula: P(g,c)=(μ1−μ2)/(σ1+σ2).

In the above formula, for P(g,c), P represents correlation coefficient between expression for gene, g, and the sensitivity/resistance classification, c; μ1 represents the mean polynucleotide expression level of samples in class 1; μ2 represents the mean polynucleotide expression level of samples in class 2; σ1 represents the standard deviation of polynucleotide expression for samples in class 1; and σ2 represents the standard deviation of polynucleotide expression for samples in class 2.

Large values of P(g,c) indicate a strong correlation between polynucleotide expression and resistance/sensitivity classification. When the correlation is compared to that of a random permutation test (randomly assigned classification), a significance measurement p-value is obtained. Then, the polynucleotides can be ranked according to the correlation coefficient obtained from this analysis, with the highest value indicating the best correlation of polynucleotide expression level with the resistance/sensitivity classification to the protein tyrosine kinase inhibitor compound in the twenty-three breast cell lines.

The KNN analysis demonstrated that hundreds of polynucleotides correlated to the drug resistance/sensitivity classification for the compound. Therefore, for greater stringency, three different methods were applied to select a smaller subset of polynucleotides that correlated with the drug resistance/sensitive classification for the compound:

First, a permutation test was performed to calculate the significance of the correlation coefficients obtained in the above-described KNN analysis. 350 polynucleotides whose ‘p’ value was less than or equal to 0.01 were selected. Second, the Pearson correlation coefficient (a dimensionless index that ranges from −1.0 to 1.0), was calculated, in which the IC₅₀ data were considered as a continuous variable and a linear regression model was utilized to correlate polynucleotide expression level with IC₅₀ values for the twenty-three breast cell lines. Those polynucleotides with a correlation coefficient greater than 0.35 or less than −0.35 were selected (p<0.05). Finally, Welch t-test was performed, the polynucleotides with p-values equal to or less than 0.05 were selected.

When the three analyses were performed to select polynucleotides correlated with the drug resistance/sensitivity classification for compound BMS-A, the polynucleotide lists from the three analysis methods were obtained and compared. It was observed that there were 168 polynucleotides overlapped from the three analyses. Of these, 32 polynucleotides were redundantly represented more than once on the 168 polynucleotide list, and removed to just leaving one copy per unique gene. Therefore, 137 unique polynucleotides are identified and listed in Table 2. There are 68 polynucleotides highly expressed in the cell lines that were classified as sensitive to BMS-A, while 69 polynucleotides are highly expressed in the cell lines that were classified as resistant to BMS-A. Examples of the polynucleotides include caveolin-1, caveolin-2, and annexin A1 and annexin A2, which are substrates for src tyrosine kinase (M. T. Brown and J. A. Cooper, 1996, Biochemica et Biophysica Acta, 1287:121-149). EphA2 and EphB2 are tyrosine kinase receptors, they have diverse roles in carcinopolynucleotidesis (M. Nakamoto and A. D. Bergemann, 2002, Microscopy Research and Technique 59:58-67).

Identification of Polynucleotides Modulated by Drug Treatment

To identify polynucleotides regulated by a protein tyrosine kinase inhibitor compound, e.g., BMS-A, 11 breast cell lines (indicated in bold in the Table 1) having an IC₅₀ ranging from 0.0055 to 9.5 μM were used in a drug treatment study. Cells were treated with or without the BMS-A compound (0.4 μM) in 0.1% DMSO for 24 hours. Expression profiling was performed, and the data were analyzed using GeneChip® Expression Analysis software MAS 5.0 (Affymetrix, Santa Clara, Calif.). The polynucleotide expression of a cell line treated with drug was compared pair-wisely to the polynucleotide expression of the same cell line without drug treatment. A change in p-value was calculated, indicating an increase, decrease or no change in polynucleotide expression. When the p-value was less than 0.0025, the change was considered to be significant. Analysis was performed for all 11 cell lines to compare the polynucleotide expression with and without drug treatment.

In addition, a pair-wise t-test with permutation analysis was applied. Polynucleotides that were significantly modulated by the drug treatment in sensitive cell lines and/or in resistant cell lines were identified. Polynucleotides whose expression was significantly changed in at least 3 cell lines were considered to be modulated by the drug. The polynucleotides, whose expression was significantly correlated with drug resistance/sensitivity classification and modulated by drug treatment as well, are indicated in Table 2. Examples of such polynucleotides include EphA2 and caveolin-2, which were highly expressed in sensitive cells and were down regulated by treatment with the protein tyrosine kinase inhibitor compound BMS-A only in sensitive cell lines as shown in FIG. 2.

Down regulation of the marker polynucleotides by the protein tyrosine kinase inhibitor compound treatment is also seen in PC3 prostate cell line which is tested to be very sensitive to BMS-A. As illustrated in FIG. 3, a dose and time dependent polynucleotide expression decrease of EphA2 and caveolin-2 is observed when compared to the untreated control.

Since EphA2 belongs to family of tyrosine kinase receptors, it is possible to test whether cells treated with the protein tyrosine kinase inhibitor compound BMS-A would affect phosphorylation status of EphA2. Immunoblot analysis of protein level and phosphorylation status of EphA2 in nine breast tumor cell lines is shown in FIG. 4. Cells were treated with 0.1 μM of BMS-A for one hour. Cell lysates were immuno-precipitated with EphA2 antibody and blot with EphA2 antibody or anti-phosphotyrosine antibody. The results indicate that EphA2 protein level does not change upon the drug treatment for one hour, but the phosphorylation at tyrosine residue is dramatically decreased with the drug treatment. Recombinant human EphA2 protein was also tested in an in vitro kinase assay and showed auto dephosphorylation upon the protein tyrosine kinase inhibitor compound BMS-A treatment with an inhibitory IC₅₀ of 17 nM.

The identification of those polynucleotides whose expression levels are not only correlated with the sensitivity or resistance of breast cell lines to treatment with a protein tyrosine kinase inhibitor compound (e.g., BMS-A), but also differentially regulated or modified by treatment with the compound can provide additional information about biological function or activity. The expression levels of these polynucleotides are regulated, or their phosphorylation level is modulated by the inhibitor compound indicating these polynucleotides are likely to be directly or indirectly involved in one or more protein tyrosine kinase signaling pathways, for example, protein tyrosine kinases that are members of the Src family of tyrosine kinases, including Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors.

Utility of Highly Correlated Polynucleotides to Make Predictions

Polynucleotides that correlate to a specific property of a biological system can be used to make predictions about that biological system and other biological systems. The Genecluster software or other programs can be used to select polynucleotides and combinations of polynucleotides that can predict properties using a “weighted-voting cross-validation algorithm” (T. R. Golub et al., 1999, Science, 286:531-537). In particular, the Genecluster software was used to build predictors that demonstrate the utility of polynucleotides that correlate to drug sensitivity and resistance. As used herein, the terms “predictor” or “predictor sets” are used as follows: a predictor or a predictor set refers to a single gene, or combination of polynucleotides, whose expression pattern or properties can be used to make predictions, with different error rates, about a property or characteristic of any given biological system.

The ability of polynucleotide expression patterns to predict a resistance/sensitive classification was further investigated using a “weighted-voting cross-validation algorithm” which uses a leave one out cross-validation strategy as described by T. R. Golub et al., 1999, Science, 286:531-537. The program was formatted to select the optimal number of polynucleotides whose expression pattern could be used to predict, with optimal accuracy, the classification of a cell line based on resistance or sensitivity toward a given protein tyrosine kinase inhibitor compound, e.g., BMS-A. A brief description of the cross-validation strategy of the program is described.

Based on the leave-one-out cross-validation strategy, a total of twenty-three prediction analyses (i.e., the number of cell lines in the data set) were performed in an iterative manner and the results of all twenty-three prediction analyses were combined to select the optimal number of polynucleotides that had optimal predictive accuracy. In each separate prediction analysis, one cell line was withheld from the data set, and an optimal number polynucleotide predictor was built, based on the remaining twenty-two cell lines, and was subsequently used to predict the class of the withheld sample.

FIG. 5 shows the real error rates using different numbers of polynucleotides in the predictor set and using different selections and combinations of markers for predicting classes among the breast cell lines which were either resistant or sensitive to BMS-A. When the predictor sets were selected from the 137 polynucleotides as shown in Table 2, the lowest error rate of 6.3% was achieved in the cross-validation tests with 15 markers. Another predictor set comprised of 7 different polynucleotides selected from the 40 polynucleotides that were modulated by the drug treatment achieved an error rate of 3.1%. This result indicates that polynucleotides which are not only correlated with drug sensitivity, but also modulated by drug, can provide a better and more accurate prediction in a predictor set.

The real error rates for predicting the sensitivity class of breast cell lines to BMS-A were compared with the real error rates using the same number of polynucleotides as the predictor set in 20 cases in which classification for the breast cell lines was randomly assigned. As shown in FIG. 6, in the cross-validation tests, when the predictor set contained either 7 or 15 polynucleotides selected from different polynucleotide groups, the error rate for predicting sensitivity of BMS-A in the 23 breast cell lines was 3.1% and 6.3%, respectively. By contrast, the real error rates ranged from 30% to 83% when using same number of polynucleotides for the predictor set in 20 cases in which classification for the breast cell lines was randomly assigned. This result demonstrated that the error rate value for predicting sensitivity to BMS-A in 23 breast cell lines was significantly lower than the error rate for predicting randomly assigned classification.

Table 3 shows the prediction accuracy of the optimal 15 and 7 polynucleotide predictor sets for the resistance/sensitive classification of the twenty-three breast cell lines to BMS-A in the leave-one-out cross validation tests. When a 15 polynucleotide predictor set selected from the 137 polynucleotides which were derived from above mentioned three analysis methods (i.e., KNN, Pearson correlation between polynucleotide expression level and IC₅₀ values for the twenty-three breast cell lines, and t-test) was used in a leave-one-out cross-validation test, twenty-one out of twenty-three samples were correctly predicted and two resistant cell lines, HCC38 and MDA-MB-435S were predicted to be sensitive to BMS-A. This resulted in a 6.3% real error rate, calculated as follows:

$\frac{\left( {{{2/16}\mspace{14mu}{resistant}} + {{0/7}\mspace{14mu}{sensitive}}} \right)}{2} \times 100\%\text{)}$

When a 7 polynucleotide predictor set, selected from the 40 drug treatment modulated polynucleotides that were part of the 137 polynucleotides in Table 2, was used in a leave-one-out cross-validation test, only one resistant cell line, HCC38, was predicted to be sensitive to BMS-A. This resulted in a 3.1% real error rate, calculated as follows:

$\frac{\left( {{{1/16}\mspace{14mu}{resistant}} + {{0/7}\mspace{14mu}{sensitive}}} \right)}{2} \times 100\%\text{)}$

In addition, a Prediction Strength (“PS”) score for each prediction made on a cell line by the predictor set can be obtained from the Genecluster software. The “PS” score ranges from 0 to 1, measuring the margin of victory in each prediction using weighted-voting cross-validation algorithm (see, e.g., T. R. Golub et al., 1999, Science, 286:531-537). The higher the value of a PS score is, the more confident the prediction make. The PS score values for each cell line using the optimal 15 or 7 polynucleotide predictor set, obtained as described above for BMS-A, are shown in Table 3. Note that even though the cell line BT549 was predicted correct to be resistant with both the 15 and 7 polynucleotide predictor sets, the PS score was very low, which means the confidence of prediction is low.

It will be appreciated that the exact number of polynucleotides that should comprise an optimal predictor set is not particularly established or defined. It is unlikely in the real world that any predictor set can be obtained with 100% or absolute accuracy. This is due to the fact that there is a trade-off between the amount of additional information and robustness that are gained by adding more polynucleotides, and the amount of noise that is concomitantly added. In accordance with the present invention, different numbers of polynucleotides were tested in the predictor sets; data were obtained and analyzed for a protein tyrosine kinase inhibitor, BMS-A. The selection of marker polynucleotides for use in the prediction set was well within the total number of polynucleotides, as shown in Table 2, that strongly correlated with the sensitivity class distinction.

Thus, in accordance with the present invention, an approach has been developed in which polynucleotides and combinations of polynucleotides have been discovered whose expression pattern in a subset of cell lines correlates with, and can be used as a predictor of, response to treatment with compounds that inhibit the function of protein tyrosine kinases.

Predictor Sets, Error Rates and Algorithms Used to Demonstrate Utility

The number of polynucleotides in any given predictor or predictor set may influence the error rate of the predictor set in cross validation experiments and with other mathematical algorithms. The data show that the error rate of a predictor is somewhat dependent on the number of polynucleotides in the predictor set and the contribution of each individual polynucleotide in the given predictor set and the number of cell lines that are tested in the cross validation experiment. For example, in a given predictor set, one polynucleotide may contribute more significantly than other polynucleotides to the prediction.

It is very likely that if a polynucleotide significantly contributes to a predictor set, then it can be used in different combinations with other polynucleotides to achieve different error rates in different predictor sets. For example, polynucleotide A alone gives an error rate of 30%. In combination with polynucleotides, B, C and D, the error rate becomes 10%; in combination with polynucleotides B, D and E, the error rate becomes 12%; while a combination of polynucleotide A with polynucleotides E-X gives an error rate of 8%, and so on. As demonstrated in FIG. 5, different selection and combination of polynucleotides in a predictor set achieve different error rates in the cross-validation tests.

When the predictor sets were selected from the 137 polynucleotides as shown in Table 2, the lowest error rate of 6.3% was achieved in the cross-validation test with 15 markers as shown in Table 4. Another predictor set comprised of 7 polynucleotides (Table 5) selected from the 40 polynucleotides that were modulated by the drug treatment, achieved an error rate of 3.1%. This result indicates that polynucleotides which are not only correlated with drug sensitivity, but also modulated by the drug, can provide a better and more accurate prediction in a predictor set.

The error rates as described herein apply to the set of cell lines used in the cross-validation experiment. If a different set is used, or more cell lines are added to the original set tested, then different error rates may be obtained as described and understood by the skilled practitioner. Importantly, different combinations of polynucleotides that correlate to drug sensitivity can be used to build predictors with different prediction accuracy.

Expression Pattern of the Protein Tyrosine Kinase Biomarkers in Primary Breast Tumors

One hundred thirty-four primary breast tumor biopsies were obtained from clinic, and expression profiles of these samples were performed. The expression pattern of the 137 polynucleotides, that are highly correlated with a resistance/sensitivity phenotype classification of the 23 breast cell lines for the protein tyrosine kinase inhibitor compound BMS-A according to the present invention (as shown in FIG. 1 and Table 2), were examined in the 134 primary breast tumors as demonstrated in FIG. 7. Each row corresponds to a gene, with the columns corresponding to expression level in the different breast tumor samples. The individual polynucleotide encoding the protein tyrosine kinase biomarkers of the invention is in the same order as indicated in FIG. 1. It is clear as shown in FIG. 7 that a group of primary breast tumors (as indicated by the arrow) highly express the sensitive biomarkers of protein tyrosine kinase inhibitor of the invention. By contrast, another different group primary breast tumors highly express the resistant biomarkers. Although, whether these group of primary breast tumors highly expressing the sensitive biomarkers are really sensitive to the protein tyrosine kinase compounds, e.g., BMS-A is unknown and need to be tested, the fact that the primary breast tumors exist similar expression pattern of the protein tyrosine kinase biomarkers as the sensitive breast cell lines gives a promise clue.

Utility of Predictor Sets to Make Predictions on Testing Data of Same Tissue Type

As described herein, 137 polynucleotides (listed in Table 2) were demonstrated to have their expression levels correlated with sensitivity to a protein tyrosine kinase inhibitor, BMS-A in 23 breast cancer cell lines. The ability of these 137 polynucleotides, either individually, in combination with one or more, or a represented by polynucleotide subsets to make sensitivity and/or resistence predictions of cell lines to BMS-A was then evaluated in test samples that were different than the test samples used to identify these polynucleotides. Such test samples were utilized to further demonstrate the ability of these 137 polynucleotides, to any combination of one or more of these polynucleotides, and/or a predictor polynucleotide subset, to accurately predict the sensitivity or resistence of a particular test line to BMS-A. As demonstrated in Table 7, the IC₅₀ for each of the 12 new breast cancer cell line test samples to BMS-A was measured and the resistance/sensitivity phenotype classification of the 12 new breast cancer cell line test samples was based on their IC₅₀ results. The cell lines with a IC₅₀ below 1 μM were defined as sensitive to the compound, while those having a IC₅₀ above 1 μM were considered to be resistant. The gene expression profile for these 12 breast cancer cell line test samples was performed using Affymetrix gene chip Hu-U133 sets. When a predictor set consisting of all the 137 polynucleotides identified in original 23 breast cancer cell line test samples was used to make sensitivity predictions on the 12 new breast cancer cell line test sample based on their gene expression profile by using the “weighted-voting algorithm” within the GeneCluster software, 3 out 4 sensitive cell lines and 1 out 8 resistant cell lines were predicted correctly, resulting in a prediction accuracy of 75% and 87.5% for sensitive and resistant cell lines, respectively. The total error rate was 16.7% (2/12). Sequentially, different predictor sets comprised from the 137 polynucleotides listed in Table 2 were tested for prediction. When the 40 polynucleotides (whose expression levels are modulated by the drug treatment as indicated in Table 2) were used to build a predictor set to make senstitivity predictions on the 12 new breast cancer cell line test samples, only one of the sensitive cell lines was incorrectly predicted, resulting in an astonishing total error rate of only 8.3%. This result directly demonstrated that the predictor polynucleotides, whose expression levels are not only correlated to sensitivity to the BMS-A compound in the original 23 breast cancer cell lines but also modulated by the drug treatment, would have more power in making sensitivity predictions on additional new samples. Furthermore, when the previously identified predictor sets, that consisted of either 15 (Table 4) or 7 polynucleotides (Table 5) that gave the best prediction on the original 23 breast cancer cell lines in the leave-one-out cross validation tests (Table 3), were used in making prediction on the 12 new breast cancer cell lines, they gave the same result with 10 out of 12 samples being correctly predicted, resulting in a total error rate of 16.7% as shown in Table 7.

Based on biological function of the markers shown in Table 2 in relation to protein tyrosine kinases, especially src-family kinase related signaling pathways, and based on changes of their expression level modulated by BMS-A treatment, six polynucleotides as listed in Table 8 were selected to comprise a polynucleotide predictor set that was then utilized to make sensitivity predictions on the additional 12 breast cell line test samples. The prediction results (as shown in Table 9) demonstrated that 3 out of 4 sensitive cell lines and all 8 resistant cell lines were predicted correctly, resulting in error rates of 25% and 0% for sensitive and resistant cell lines, respectively. A total error rate of 8.3% (1/12) was achieved, with normalized error rate of 12.5% (Table 10). The p value was determined to be 0.0182 when the prediction result was evaluated using the Fisher test.

Results illustrated in Tables 7 and 9 indicate that the polynucleotide predictor sets containing either all the 137 polynucleotides (Table 2), any combinations thereof, or specific subset combinations such as those presented in Tables 4, 5 and/or 8, are able to make senstitivity predictions on test samples from in same tissue type in which they were originally identified (e.g., breast) with significant accuracy.

Utility of Polynuclelotide Predictor Sets to Make Predictions on Testing Data of Different Tissue Type

As described herein, the polynucleotides listed in Table 2 were identified from breast cancer cell lines. Furthermore, as the results described herein demonstrate, the predictor polynucleotides are able to accurately predict the sensitivity and/or resistence of breast cancer cell line test samples to exposure to BMS-A. However, it would also be important to demonstrate that these predictor polynucleotides are also able to predict the sensitivity and/or resistence of cancer cell line test samples to exposure to BMS-A derived from a tissue type other than breast tissue. Table 11 provides the resistance/sensitivity phenotype classification of 23 lung cancer cell line test samples for BMS-A as determined based upon their IC₅₀ results. The cell lines with a IC₅₀ below 1 μM were defined as sensitive to the compound, while those having a IC₅₀ above 1 μM were considered to be resistant. When the predictor polynucleotide set of 6 polynucleotides (Table 8) was used to make sensitivity predictions to BMS-A on these 23 lung cancer cell lines, 10 out of 11 sensitive cell lines and 9 out of 12 resistant cell lines were predicted correctly, resulting in prediction accuracies of 91% and 75% for sensitive and resistant cell lines, respectively. One sensitive and 3 resistant cell lines were predicted incorrectly with a normalized error rate of 17% (Table 12). The prediction results were evaluated using the Fisher test with a calculated p-value of 0.00276. This result clearly demonstrates that the predictor set of 6 polynucleotides (Table 8) is able to make sensitivity predictions not only in breast cancer cell lines, but also in lung cancer cell lines. Therefore, the predictor sets validate cross different tissue types.

Thus, in accordance with the present invention, an approach has been developed in which predictor polynucleotides, and/or combinations of predictor polynucleotides, have been discovered whose expression pattern in a subset of breast cell lines correlates with response to treatment with compounds that inhibit the function of protein tyrosine kinases, and can be used as in predicting additional samples of same tissue types (breast), as well as different tissue types (lung), among others. It is expected that these predictor polynucleotides will be useful in predicting the sensitivity and/or resistence of other tissue types, including, but not limited to, colon, and prostate, tissue, and in particular, colon cancer and prostate cancer tissues.

Inhibition of Src Expression by Antisense or RNAi Also Decrease Expression of Some Markers

Markers, such as EphA2 and caveolin are shown to be down regulated by exposure to the BMS-A compound (see FIG. 2) through inhibition of the activity of protein tyrosine kinases, such as Src and Src-family kinases as described herein. Antisense or RNAi experiments to block Src expression were performed to assess whether such expression inihibition has the same effect on expression of the polynucleotide predictor markers as exposure to the protein tyrosine kinase inhibitor BMS-A. In the antisense experiment shown in FIG. 8, two negative control antisense (NC-AS) oligos (NC-18029 and NC-18030) or three Src specific antisense (Src-AS) oilgos (Src-AS-18025, Src-AS-18028 and Src-AS-18032) made by Sequitur Inc. were used to transfect a lung cancer cell line A549. The transfection was done in triplicate. After 24 hours, cells from each transfection experiment were harvested for RNA preparation, which was then used in quantitative RT-PCR assays to measure the expression of Src and EphA2 genes. The expression of Src and EphA2 was normalized to the expression of the GAPDH gene, and the values shown in the FIG. 8 represented the average of RT-PCR results (triplicate RT-PCR reactions for each of 3 transfection experiments of either two NC-AS oligos or three different Src-AS oligos). The results indicated that Src expression was down-regulated 60-65% by three Src-AS oligos, while EphA2 expression was down-regulated 10-60% in Src-AS transfected cells compared to NC-AS oligos. The significance between the expression difference in NC-AS and Src-AS transfected cells for both Src and EphA2 genes was compared using a t-test. The p-values were calculated to be 0.00005 and 0.038 for Src and EphA2 expression, respectively.

In another experiment, Src expression was inhibited using RNAi reagents specific to the Src kinase gene, and then the expression of CAV-1 was monitored. As shown in FIG. 9, five Src specific RNAi reagents (1-4 and SP, which is smart pool of several RNAi) and a negative control (GFP B RNAi reagent) all made by Dharmacon, Inc., were used to transfect Hela cell. Forty-eight hours post-transfection, cells were lysed and proteins were isolated for Western blot analysis by blotting with both Src and PCNA antibodies (FIG. 9A) or CAV-1 and PCNA antibodies (FIG. 9C). PCNA protein was used as an internal control for protein loading, and the level of Src or caveolin 1 was normalized to the level of PCNA. The percentage of inhibition was calculated by comparing the ratio of Src/PCNA or CAV-1/PCNA from each of the Src-RNAi reagent transfected cells to the ratio from the negative control, which was transfected by RNAi directed to GFP B. As shown in FIG. 9B, the Src expression was inhibited from 24 to 64% in different Src-RNAi transfectants, while CAV-1 was inhibited by 13 to 56% (FIG. 9D). CAV-1 expression was decreased to a certain extent whenever Src was down-regulated, even though there was no direct correlation between the percentage of Src inhibition and percentage of CAV-1 down regulation. As demonstrated by both the drug treatment experiments using the protein kinase inhibitor compound, BMS-A, in addition to the RNAi or antisense experiments, it is evident that inhibition of both activity and expression of the Src protein results in statistically significant down regulation of polynuclelotide predictor markers, in general, and for EphA2 and CAV-1, in particular.

Validate Gene Expression Pattern by Quantitative RT-PCR

To test whether the gene expression pattern measured by Affymetric Genechip can be cross validated by another technology platform, the expression of 4 selected predictor markers (EphA2, EphB2, CAV-1 and CAV-2) was further evaluated by quantitative RT-PCR assays using RNA derived from the same 23 breast cell lines that were used to identify the predictor markers using gene expression profile analysis as described herein. Each RT-PCR experiment was performed in triplicate. The expression of the selected 4 predictor markers was normalized to the expression of the GAPDH gene. The relative expression level (relative to MDA-MB-157, set to 1000) of each predictor marker for each cell line measured by both Affymetrix Genechip and quantitative RT-PCR is illustrated in FIG. 10. A good correlation between the results measured by Affymetrix Genechip and quantitative RT-PCR was observed as measured by Pearson correlation coefficients with calculated values of 0.80, 0.93, 0.69 and 0.80 for EphA2, EphB2, CAV-1 and CAV-2, respectively. When the expression level of each predictor marker was compared between sensitive and resistant breast cell lines as defined in Table 1 by t-test for the data from both Affymetrix Genechip and quantitative RT-PCR, the results shown in Table 13 indicated that they are all statistically significant with the sole exception of CAV-1 measured by RT-PCR, which has p value of 0.0738. These results demonstrate that both Affymetrix Genechip and quantitative RT-PCR, can be used in measuring gene expression levels for the predictor markers listed in Table 2.

Protein Expression of Markers in Breast Cell Lines Measured by Immunohistochemistry (IHC) Assay

As demonstated in the results shown in FIG. 10 and Table 13, both Affymetrix Genechip and quantitative RT-PCR methods were shown to produce expression results with statistically good correlations between both methods, in the 23 breast cell lines that were originally used to identify the potential prediction markers. To test whether the protein level of the cell lines are correlated with RNA expression level, IHC assays were utilized to evaluate the protein expression of selected predictor markers (EphA2 and CAV-1). Five breast cancer cell lines were selected from the 23 cell lines according to their sensitivity to the BMS-A compound and used to make slides for IHC assay. As illustrated in FIG. 11, cytoplasmic localization of both EphA2 and CAV-1 in multiple breast cell lines was observed, with higher expression in sensitive cell lines (MDAMB231 and MDAMB 157) and lower expression in resistant lines (BT474, MCF7 and ZR-75-1). This observation demonstrates that the protein level of the two predictor markers was also correlated with the sensitivity of cell lines to BMS-A compound. Furthermore, these results were also consistent with the results obtained from RNA expression of these two genes as measured by both Affymetrix Genechip and quantitative RT-PCR, indicating that these predictor markers are capable of accurately predicting the efficacy to BMS-A, and/or other protein tyrosone kinase inhibitors, at both the RNA and protein level. It is expected that each of the other predictor polynucleotides, including any combinations thereof, including, but not limited to, the predictor polynucleotide subsets provided in Tables 4, 5, and/or 8, are also capable of accurately predicting the efficacy to BMS-A, and/or other protein tyrosone kinase inhibitors, at both the RNA and protein level, as well.

Applications of Predictor Sets

Predictor sets with different error rates can be used in different applications. Predictor sets can be built from any combination of the polynucleotides listed in Table 2, or the predictor polynucleotide subsets of 40, 15, 7, and 6 polynucleotides, as presented in each of Tables 2, 4, 5, and 8 respectively, to make predictions about the likely effect of protein tyrosine modulator compounds, e.g., inhibitors, or compounds that affect a protein tyrosine kinase signaling pathway in different biological systems. The various predictor sets described herein, or the combination of these predictor sets with other polynucleotides or other co-variants of these polynucleotides, can have broad utility. For example, the predictor sets can be used as diagnostic or prognostic indicators in disease management; they can be used to predict how patients with cancer might respond to therapeutic intervention with compounds that modulate the protein tyrosine kinase family (e.g., the src tyrosine kinase family); and they can be used to predict how patients might respond to therapeutic intervention that modulate signaling through an entire protein tyrosine kinase regulatory pathway, such as, for example, the src tyrosine kinase regulatory pathway.

While the data described herein were generated in cell lines that are routinely used to screen for and identify compounds that have potential utility for cancer therapy, the predictors can have both diagnostic and prognostic value in other diseases areas in which signaling through a protein tyrosine kinase or a protein tyrosine kinase pathway is of importance, e.g., in immunology, or in cancers or tumors in which cell signaling and/or proliferation controls have gone awry. Such protein tyrosine kinases and their pathways comprise, for example, members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. Although the data described herein have been generated using the particularly exemplified protein tyrosine kinase inhibitor compound, BMS-A, three other protein tyrosine kinase inhibitor compounds were tested in addition to BMS-A and were found to have similar sensitivity and resistance classifications in the 23 breast cell lines evaluated. Thus, the predictors can have both diagnostic and prognostic value related to other inhibitor molecules, as well as any molecules or therapeutic interventions that affect protein tyrosine kinases, such as Src tyrosine kinase, or a protein tyrosine kinase signaling pathways, such as that of the Src tyrosine kinase.

Those having skill in the pertinent art will appreciate that protein tyrosine kinase pathways, e.g., the Src tyrosine kinase pathway, are present and functional in cell types other than cell lines of breast tissue. Therefore, the described predictor set of polynucleotides, or combinations of polynucleotides within the predictor set, can show utility for predicting drug sensitivity or resistance to compounds that interact with, or inhibit, a protein tyrosine kinase activity in cells from other tissues or organs associated with a disease state, or cancers or tumors derived from other tissue or organ types. Non-limiting examples of such cells, tissues and organs include colon, breast, lung, heart, prostate, testes, ovaries, cervix, esophagus, pancreas, spleen, liver, kidney, intestine, stomach, lymphocytic and brain, thereby providing a broad and advantageous applicability to the predictor polynucleotide sets described herein. Cells for analysis can be obtained by conventional procedures as known in the art, for example, tissue or organ biopsy, aspiration, sloughed cells, e.g., colonocytes, clinical or medical tissue, or cell sampling procedures.

Functionality of Polynucleotides that Make Up a Predictor Set

The use of a predictor, or predictor set, (e.g., predictor polynucleotides, or a predictor set of polynucleotides) allows for the prediction of an outcome prior to having any knowledge about a biological system. Essentially, a predictor can be considered to be a tool that is useful in predicting the phenotype that is used to classify the biological system. In the specific embodiment provided by the present invention, the classification as “resistant” or “sensitive” is based on the IC₅₀ value of each cell line to a compound (e.g., the protein tyrosine kinase inhibitor compound BMS-A as exemplified herein), relative to the mean log₁₀(IC₅₀) value of the cell line panel (e.g., a twenty-three breast cell line panel, as exemplified herein).

As a particular example, a number of the polynucleotides described herein (Table 2) are known to be substrates for the src tyrosine kinase family, e.g., caveolin-1 and caveolin-2 (M. T. Brown and J. A. Cooper, 1996, Biochemica et Biophysica Acta, 1287:121-149). EphA2 is a tyrosine kinase receptor. The data presented herein demonstrated that EphA2 is highly expressed in the sensitive cell lines, and its expression level and activity are down regulated by treatment of the protein tyrosine kinase inhibitor compound BMS-A. This is expected, since polynucleotides that contribute to a high predictor accuracy are likely to play a functional role in the pathway that is being modulated. For example, Herceptin therapy (i.e., antibody that binds to the Her2 receptor and prevents function via internalization) is indicated when the Her2 polynucleotide is overexpressed. It is unlikely, although not impossible, that a therapy will have a therapeutic effect if the target enzyme is not expressed.

However, although the complete function of all of the polynucleotides and their functional products (proteins and mRNAs) that make up a predictor set are not currently known, some of the polynucleotides are likely to be directly or indirectly involved in a protein tyrosine kinase signaling pathway, such as the Src tyrosine kinase signaling pathway. In addition, some of the polynucleotides in the predictor set may function in the metabolic or other resistance pathways specific to the compounds being tested. Notwithstanding, a knowledge about the function of the polynucleotides is not a requisite for determining the accuracy of a predictor according to the practice of the present invention.

As described herein, polynucleotides have been discovered that correlate to the relative intrinsic sensitivity or resistance of breast cell lines to treatment with compounds that interact with and inhibit protein tyrosine kinases, e.g., Src tyrosine kinase. These polynucleotides have been shown, through a weighted voting, leave-one-out, cross validation program, to have utility in predicting the intrinsic resistance and sensitivity of breast cell lines to these compounds.

An embodiment of the present invention relates to a method of determining or predicting if an individual requiring drug or chemotherapeutic treatment or therapy for a disease, for example, a breast cancer or a breast tumor, will be likely to successfully respond or not respond to the drug or chemotherapeutic agent prior to subjecting the individual to such treatment or chemotherapy. The drug or chemotherapeutic agent can be one that modulates a protein tyrosine kinase activity or signaling involving a protein tyrosine kinase. Nonlimiting examples of such protein tyrosine kinases include members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. In accordance with the method of the invention, cells from a tissue or organ associated with disease, e.g., a patient biopsy of a tumor or cancer, preferably a breast cancer or tumor biopsy, are subjected to an in vitro assay as described herein, to determine their marker polynucleotide expression pattern (polynucleotides from Table 2 and/or the predictor polynucleotide subsets of Tables 4-5) prior to their treatment with the compound or drug, preferably an inhibitor of a protein tyrosine kinase. The resulting polynucleotide expression profile of the cells before drug treatment is compared with the polynucleotide expression pattern of the same polynucleotides in cells that are either resistant or sensitive to the drug or compound, as provided by the present invention.

In another related embodiment, the present invention includes a method of predicting, prognosing, diagnosing, and/or determining whether an individual requiring drug therapy for a disease state or chemotherapeutic for cancer (e.g., breast cancer) will or will not respond to treatment prior to administration of treatment. The treatment or therapy preferably involves a protein tyrosine kinase modulating agent, compound, or drug, for example, an inhibitor of the protein tyrosine kinase activity. Protein tyrosine kinases include, without limitation, members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. Preferred is src tyrosine kinase and inhibitors thereof. In accordance with this embodiment, cells from a patient's tissue sample, e.g., a breast tumor or cancer biopsy, are assayed to determine their polynucleotide expression pattern prior to treatment with the protein tyrosine kinase modulating agent, compound, or drug. The resulting polynucleotide expression profile of the test cells before exposure to the compound or drug is compared with that of one or more of the predictor subsets of polynucleotides comprising either 40, 15, 7, or 6 polynucleotides as described herein and shown in Tables 2, Tables 4-5, and Table 8, respectively.

Success or failure of treatment of a patient's cancer or tumor with the drug can be determined based on the polynucleotide expression pattern of the patient's cells being tested, compared with the polynucleotide expression pattern of the predictor polynucleotides in the resistant or sensitive panel of that have been exposed to the drug or compound and subjected to the predictor polynucleotide analysis detailed herein. Thus, if following exposure to the drug, the test cells show a polynucleotide expression pattern corresponding to that of the predictor polynucleotide set of the control panel of cells that is sensitive to the drug or compound, it is highly likely or predicted that the individual's cancer or tumor will respond favorably to treatment with the drug or compound. By contrast, if, after drug exposure, the test cells show a polynucleotide expression pattern corresponding to that of the predictor polynucleotide set of the control panel of cells that is resistant to the drug or compound, it is highly likely or predicted that the individual's cancer or tumor will not respond to treatment with the drug or compound.

In a related embodiment, screening assays are provided for determining if a patient's cancer or tumor is or will be susceptible or resistant to treatment with a drug or compound, particularly, a drug or compound directly or indirectly involved in protein tyrosine kinase activity or a protein tyrosine kinase pathway, e.g., the Src tyrosine kinase activity or pathway.

Also provided by the present invention are monitoring assays to monitor the progress of a drug treatment involving drugs or compounds that interact with or inhibit protein tyrosine kinase activity. Protein tyrosine kinases encompassed by these monitoring assays include members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. Such in vitro assays are capable of monitoring the treatment of a patient having a disease treatable by a compound or agent that modulates or interacts with a protein tyrosine kinase by comparing the resistance or sensitivity polynucleotide expression pattern of cells from a patient tissue sample, e.g., a tumor or cancer biopsy, preferably a breast cancer or tumor sample, prior to treatment with a drug or compound that inhibits the protein tyrosine kinase activity and again following treatment with the drug or compound with the expression pattern of one or more of the predictor polynucleotide sets described, or combinations thereof. Isolated cells from the patient are assayed to determine their polynucleotide expression pattern before and after exposure to a compound or drug, preferably a protein tyrosine kinase inhibitor, to determine if a change of the polynucleotide expression profile has occurred so as to warrant treatment with another drug or agent, or discontinuing current treatment. The resulting polynucleotide expression profile of the cells tested before and after treatment is compared with the polynucleotide expression pattern of the predictor set of polynucleotides that have been described and shown herein to be highly expressed in cells that are either resistant or sensitive to the drug or compound. Alternatively, a patient's progress related to drug treatment or therapy can be monitored by obtaining a polynucleotide expression profile as described above, only after the patient has undergone treatment with a given drug or therapeutic compound. In this way, there is no need to test a patient sample prior to treatment with the drug or compound.

Such a monitoring process can indicate success or failure of a patient's treatment with a drug or compound based on the polynucleotide expression pattern of the cells isolated from the patient's sample, e.g., a tumor or cancer biopsy, as being relatively the same as or different from the polynucleotide expression pattern of the predictor polynucleotide set of the resistant or sensitive control panel of cells that have been exposed to the drug or compound and assessed for their polynucleotide expression profile following exposure. Thus, if, after treatment with a drug or compound, the test cells show a change in their polynucleotide expression profile from that seen prior to treatment to one which corresponds to that of the predictor polynucleotide set of the control panel of cells that are resistant to the drug or compound, it can serve as an indicator that the current treatment should be modified, changed, or even discontinued. Also, should a patient's response be one that shows sensitivity to treatment by a protein tyrosine kinase inhibitor compound, e.g., a Src tyrosine kinase inhibitor, based on correlation of the expression profile of the predictor polynucleotides of cells showing drug sensitivity with the polynucleotide expression profile from cells from a patient undergoing treatment, the patient's treatment prognosis can be qualified as favorable and treatment can continue. Further, if a patient has not been tested prior to drug treatment, the results obtained after treatment can be used to determine the resistance or sensitivity of the cells to the drug based on the polynucleotide expression profile compared with the predictor polynucleotide set.

In a related embodiment, the present invention embraces a method of monitoring the treatment of a patient having a disease treatable by a compound or agent that modulates a protein tyrosine kinase, i.e., breast cancer. Protein tyrosine kinases encompassed by such treatment monitoring assays include members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. For these assays, test cells from the patient are assayed to determine their polynucleotide expression pattern before and after exposure to a protein tyrosine kinase inhibitor compound or drug. The resulting polynucleotide expression profile of the cells tested before and after treatment is compared with the polynucleotide expression pattern of the predictor set of polynucleotides that have been described and shown herein to be highly expressed in cells that are either resistant or sensitive to the drug or compound. Thus, if a patient's response is or becomes one that is sensitive to treatment by a protein tyrosine kinase inhibitor compound, based on correlation of the expression profile of the predictor polynucleotides, the patient's treatment prognosis can be qualified as favorable and treatment can continue. Also, if after treatment with a drug or compound, the test cells do not exhibit a change in their polynucleotide expression profile to a profile that corresponds to that of the control panel of cells that are sensitive to the drug or compound, this serves as an indicator that the current treatment should be modified, changed, or even discontinued. Such monitoring processes can be repeated as necessary or desired and can indicate success or failure of a patient's treatment with a drug or compound, based on the polynucleotide expression pattern of the cells isolated from the patient's sample. The monitoring of a patient's response to a given drug treatment can also involve testing the patient's cells in the assay as described, only after treatment, rather than before and after treatment, with drug or active compound.

In a preferred embodiment, the present invention embraces a method of monitoring the treatment of a patient having a disease treatable by a compound or agent that modulates a src tyrosine kinase, i.e., breast cancer. The test cells from the patient are assayed to determine their polynucleotide expression pattern before and after exposure to a src tyrosine kinase inhibitor compound or drug. The resulting polynucleotide expression profile of the cells tested before and after treatment is compared with the polynucleotide expression pattern of the predictor set of polynucleotides that have been described and shown herein to be highly expressed in cells that are either resistant or sensitive to the drug or compound. Thus, if a patient's response is or becomes one that is sensitive to treatment by a src tyrosine kinase inhibitor compound, based on correlation of the expression profile of the predictor polynucleotides, the patient's treatment prognosis can be qualified as favorable and treatment can continue. Also, if after treatment with a drug or compound, the test cells do not exhibit a change in their polynucleotide expression profile to a profile that corresponds to that of the control panel of cells that are sensitive to the drug or compound, this serves as an indicator that the current treatment should be modified, changed, or even discontinued. Such monitoring processes can be repeated as necessary or desired and can indicate success or failure of a patient's treatment with a drug or compound, based on the polynucleotide expression pattern of the cells isolated from the patient's sample. The monitoring of a patient's response to a given drug treatment can also involve testing the patient's cells in the assay as described only after treatment, rather than before and after treatment, with drug or active compound.

In another embodiment, the present invention encompasses a method of classifying whether a biological system, preferably cells from a tissue, organ, tumor or cancer of an afflicted individual, will be resistant or sensitive to a compound that modulates the system. In a preferred aspect of this invention, the sensitivity or resistance of cells, e.g., those obtained from a tumor or cancer, to a protein tyrosine kinase inhibitor compound, or series of compounds, e.g., a Src tyrosine kinase inhibitor, is determined. Inhibitors can include those compounds, drugs, or biological agents that inhibit, either directly or indirectly, the protein tyrosine kinases as described previously hereinabove. According to the method, a resistance/sensitivity profile of the cells after exposure to the protein tyrosine kinase inhibitor drug or compound can be determined via polynucleotide expression profiling protocols set forth herein. Such resistance/sensitivity profile of the cells reflects an IC₅₀ value of the cells to the compound(s) as determined using a suitable assay, such as an in vitro cytotoxicity assay as described in Example 1. A procedure of this sort can be performed using a variety of cell types and compounds that interact with the protein tyrosine kinase, or affect its activity in the signaling pathway of the protein tyrosine kinase.

In another of its embodiments, the present invention includes the preparation of one or more specialized microarrays (e.g., oligonucleotide microarrays or cDNA microarrays) comprising all of the polynucleotides in Tables 2, 4, 5, or 8, or any combinations thereof, of the predictor polynucleotide sets described herein that have been demonstrated to be most highly correlated with sensitivity (or resistance) to protein tyrosine kinase modulators, particularly inhibitors of src tyrosine kinase. Preferably, the predictor polynucleotide sets are common for predicting sensitivity among more than one protein tyrosine kinase modulator, e.g. a protein tyrosine kinase inhibitor such as a Src tyrosine kinase inhibitor, as demonstrated herein. In accordance with this aspect of the invention, the oligonucleotide sequences or cDNA sequences include any of the predictor polynucleotides or polynucleotide combinations as described herein, which are highly expressed in resistant or sensitive cells, and are contained on a microarray, e.g., a oligonucleotide microarray or cDNA microarray in association with, or introduced onto, any supporting material, such as glass slides, nylon membrane filters, glass or polymer beads, chips, plates, or other types of suitable substrate material.

Cellular nucleic acid, e.g., RNA, is isolated either from cells undergoing testing after exposure to a drug or compound that interacts with a protein tyrosine kinase as described herein, or its signaling pathway, or from cells being tested to obtain an initial determination or prediction of the cells' sensitivity to the drug or compound, and, ultimately, a prediction of treatment outcome with the drug or compound. The isolated nucleic acid is appropriately labeled and applied to one or more of the specialized microarrays. The resulting pattern of polynucleotide expression on the specialized microarray is analyzed as described herein and known in the art. A pattern of polynucleotide expression correlating with either sensitivity or resistance to the drug or compound is able to be determined, e.g., via comparison with the polynucleotide expression pattern as shown in FIG. 1 for the panel of cells exposed to the protein tyrosine kinase inhibitor assayed herein.

In accordance with the specialized microarray embodiment of this invention, the microarray contains the polynucleotides of one or more of the predictor polynucleotide set(s) or subset(s), or a combination thereof, or all of the polynucleotides in Tables 2, 4, 5, or 8, that are highly correlated with drug sensitivity or resistance by a breast cell type. If the nucleic acid target isolated from test cells, such as tumor or cancer cells, preferably breast cancer or tumor cells, shows a high level of detectable binding to the polynucleotides of the predictor set for drug sensitivity relative to control, then it can be predicted that a patient's cells will respond to the drug, or a series of drugs, and that the patient's response to the drug, or a series of drugs, will be favorable.

Such a result predicts that the cells of a tumor or cancer are good candidates for the successful treatment or therapy utilizing the drug, or series of drugs. Alternatively, if the nucleic acid target isolated from test cells shows a high level of detectable binding to the polynucleotides of the predictor set for drug resistance, relative to control, then it can be predicted that a patient is likely not to respond to the drug, or a series of drugs, and that the patient's response to the drug, or a series of drugs, is not likely to be favorable. Such a result predicts that the cells of a tumor or cancer are not good candidates for treatment or therapy utilizing the drug, or series of drugs.

The utilization of microarray technology is known and practiced in the art. Briefly, to determine polynucleotide expression using microarray technology, polynucleotides, e.g., RNA, DNA, cDNA, preferably RNA, are isolated from a biological sample, e.g., cells, as described herein for breast cells, using procedures and techniques that are practiced in the art. The isolated nucleic acid is detectably labeled, e.g., fluorescent, enzyme, radionuclide, or chemiluminescent label, and applied to a microarray, e.g., the specialized microarrays provided by this invention. The array is then washed to remove unbound material and visualized by staining or fluorescence, or other means known in the art depending on the type of label utilized.

In another embodiment of this invention, the predictor polynucleotides (Table 2), or one or more subsets of polynucleotides comprising the predictor polynucleotide sets (e.g., Tables 4-5) can be used as biomarkers for cells that are resistant or sensitive to protein tyrosine kinase inhibitor compounds, e.g., Src tyrosine kinase inhibitors. With the predictor polynucleotides in hand, screening and detection assays can be carried out to determine whether or not a given compound, preferably a protein tyrosine kinase inhibitor compound such as a Src tyrosine kinase inhibitor compound, elicits a sensitive or a resistant phenotype following exposure of cells, e.g., cells taken from a tumor or cancer biopsy sample, such as a breast cancer cell sample, to the compound. Thus, methods of screening, monitoring, detecting, prognosing and/or diagnosing to determine the resistance or sensitivity of cells to a drug or compound that interacts with a protein tyrosine kinase, or a protein tyrosine kinase pathway, preferably an inhibitor compound, and to which the cells are exposed, are encompassed by the present invention.

Such methods embrace a variety of procedures and assays to determine and assess the expression of polynucleotides, in particular, the predictor or src biomarker polynucleotides and predictor polynucleotide subsets as described herein (Tables 2, 4, 5, or 8), in cells that have been exposed to drugs or compounds that interact with or effect a protein tyrosine kinase, or a protein tyrosine kinase pathway, wherein the protein tyrosine kinases include members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. Suitable methods include detection and evaluation of polynucleotide activation or expression at the level of nucleic acid, e.g., DNA, RNA, mRNA, and detection and evaluation of encoded protein. For example, PCR assays as known and practiced in the art can be employed to quantify RNA or DNA in cells being assayed for susceptibility to drug treatment, for example, protein tyrosine kinase inhibitors. (see Example 2, RT-PCR).

In another embodiment, the present invention is directed to a method of identifying cells, tissues, and/or patients that are predicted to be resistant to either protein tyrosine inhibitor compounds or compounds that affect protein tyrosine kinase signaling pathways, e.g., Src tyrosine kinase, or that are resistant in different biological systems to those compounds. The method comprises the step(s) of (i) analyzing the expression of only those polynucleotides listed in Tables 2, 4, 5, or 8, or any combination thereof, that have been shown to be correlative to predicting resistant responses to such compounds; (ii) comparing the observed expression levels of those correlative resistant polynucleotides in the test cells, tissues, and/or patients to the expression levels of those same polynucleotides in a cell line that is known to be resistant to the compounds; and (iii) predicting whether the cells, tissues, and/or patients are resistant to the compounds based upon the overall similarity of the observed expression of those polynucleotides in step (ii).

In another embodiment, the present invention is directed to a method of identifying cells, tissues, and/or patients that are predicted to be sensitive to either protein tyrosine inhibitor compounds or compounds that affect protein tyrosine kinase signaling pathways, e.g., the Src tyrosine kinase, or that are sensitive in different biological systems to those compounds. The method involves the step(s) of (i) analyzing the expression of only those polynucleotides listed in Tables 2, 4, 5, or 8, or any combination thereof, that have been shown to be correlative to predicting sensitive responses to such compounds; (ii) comparing the observed expression levels of those correlative sensitive polynucleotides in the test cells, tissues, and/or patients to the expression levels of those same polynucleotides in a cell line that is known to be sensitive to the compounds; and (iii) predicting whether the cells, tissues, and/or patients are sensitive to the compounds based upon the overall similarity of the observed expression of those polynucleotides in step (ii).

The present invention further encompasses the detection and/or quantification of one or more of the protein tyrosine kinase biomarker proteins of the present invention using antibody-based assays (e.g., immunoassays) and/or detection systems. As mentioned, protein tyrosine kinases encompass members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. Such assays include the following non-limiting examples, ELISA, immunofluorescence, fluorescence activated cell sorting (FACS), Western Blots, etc., as further described herein.

In another embodiment, the human protein tyrosine kinase biomarker polypeptides and/or peptides of the present invention, or immunogenic fragments or oligopeptides thereof, can be used for screening therapeutic drugs or compounds in a variety of drug screening techniques. The fragment employed in such a screening assay can be free in solution, affixed to a solid support, borne on a cell surface, or located intracellularly. The reduction or abolition of activity of the formation of binding complexes between the biomarker protein and the agent being tested can be measured. Thus, the present invention provides a method for screening or assessing a plurality of compounds for their specific binding affinity with a protein kinase inhibitor biomarker polypeptide, or a bindable peptide fragment thereof, of this invention. The method comprises the steps of providing a plurality of compounds; combining the protein kinase inhibitor biomarker polypeptide, or a bindable peptide fragment thereof, with each of the plurality of compounds, for a time sufficient to allow binding under suitable conditions; and detecting binding of the biomarker polypeptide or peptide to each of the plurality of test compounds, thereby identifying the compounds that specifically bind to the biomarker polypeptide or peptide. More specifically, the biomarker polypeptide or peptide is that of a Src tyrosine kinase inhibitor biomarkers.

Methods to identify compounds that modulate the activity of the human protein tyrosine kinase biomarker polypeptides and/or peptides provided in Table 2 by the present invention, comprise combining a candidate compound or drug modulator of protein kinases and measuring an effect of the candidate compound or drug modulator on the biological activity of the protein kinase inhibitor biomarker polypeptide or peptide. Such measurable effects include, for example, a physical binding interaction; the ability to cleave a suitable protein kinase substrate; effects on a native and cloned protein kinase biomarker-expressing cell line; and effects of modulators or other protein kinase-mediated physiological measures.

Another method of identifying compounds that modulate the biological activity of the protein tyrosine kinase biomarker polypeptides of the present invention comprises combining a potential or candidate compound or drug modulator of a protein tyrosine kinase biological activity, e.g., a Src tyrosine kinase, with a host cell that expresses the protein tyrosine kinase biomarker polypeptide and measuring an effect of the candidate compound or drug modulator on the biological activity of the protein tyrosine kinase biomarker polypeptides. The host cell can also be capable of being induced to express the protein tyrosine kinase biomarker polypeptide, e.g., via inducible expression. Physiological effects of a given modulator candidate on the protein tyrosine kinase biomarker polypeptide can also be measured. Thus, cellular assays for particular protein tyrosine kinase modulators, e.g., a src kinase modulator, can be either direct measurement or quantification of the physical biological activity of the protein tyrosine kinase biomarker polypeptide, or they may be measurement or quantification of a physiological effect. Such methods preferably employ a protein tyrosine kinase biomarker polypeptide as described herein, or an overexpressed recombinant protein tyrosine kinase biomarker polypeptide in suitable host cells containing an expression vector as described herein, wherein the protein tyrosine kinase biomarker polypeptide is expressed, overexpressed, or undergoes up-regulated expression.

Another aspect of the present invention embraces a method of screening for a compound that is capable of modulating the biological activity of a protein tyrosine kinase biomarker polypeptide, e.g., a Src kinase biomarker polypeptide. The method comprises providing a host cell containing an expression vector harboring a nucleic acid sequence encoding a protein tyrosine kinase biomarker polypeptide, or a functional peptide or portion thereof (e.g., the src polypeptide, protein, peptide, or fragment sequences as set forth in Table 2, or the Sequence Listing herein); determining the biological activity of the expressed protein tyrosine kinase biomarker polypeptide in the absence of a modulator compound; contacting the cell with the modulator compound and determining the biological activity of the expressed protein tyrosine kinase biomarker polypeptide in the presence of the modulator compound. In such a method, a difference between the activity of the protein tyrosine kinase biomarker polypeptide in the presence of the modulator compound and in the absence of the modulator compound indicates a modulating effect of the compound.

Essentially any chemical compound can be employed as a potential modulator or ligand in the assays according to the present invention. Compounds tested as protein tyrosine kinase modulators can be any small chemical compound, or biological entity (e.g., protein, sugar, nucleic acid, or lipid). Test compounds are typically small chemical molecules and peptides. Generally, the compounds used as potential modulators can be dissolved in aqueous or organic (e.g., DMSO-based) solutions. The assays are designed to screen large chemical libraries by automating the assay steps and providing compounds from any convenient source. Assays are typically run in parallel, for example, in microtiter formats on microtiter plates in robotic assays. There are many suppliers of chemical compounds, including, for example, Sigma (St. Louis, Mo.), Aldrich (St. Louis, Mo.), Sigma-Aldrich (St. Louis, Mo.), Fluka Chemika-Biochemica Analytika (Buchs, Switzerland). Also, compounds can be synthesized by methods known in the art.

High throughput screening methodologies are particularly envisioned for the detection of modulators of the novel protein tyrosine kinase biomarker, e.g., src biomarker, polynucleotides and polypeptides described herein. Such high throughput screening methods typically involve providing a combinatorial chemical or peptide library containing a large number of potential therapeutic compounds (e.g., ligand or modulator compounds). The combinatorial chemical libraries or ligand libraries are then screened in one or more assays to identify those library members (e.g., particular chemical species or subclasses) that display a desired characteristic activity. The compounds so identified can serve as conventional lead compounds, or can themselves be used as potential or actual therapeutics.

A combinatorial chemical library is a collection of diverse chemical compounds generated either by chemical synthesis or biological synthesis, prepared by combining a number of chemical building blocks (i.e., reagents such as amino acids). As an example, a linear combinatorial library, e.g., a polypeptide or peptide library, is formed by combining a set of chemical building blocks in every possible way for a given compound length (i.e., the number of amino acids in a polypeptide or peptide compound). Millions of chemical compounds can be synthesized through such combinatorial mixing of chemical building blocks.

The preparation and screening of combinatorial chemical libraries is well known to those having skill in the pertinent art. Combinatorial libraries include, without limitation, peptide libraries (e.g. U.S. Pat. No. 5,010,175; Furka, 1991, Int. J. Pept. Prot. Res., 37:487-493; and Houghton et al., 1991, Nature, 354:84-88). Other chemistries for generating chemical diversity libraries can also be used. Nonlimiting examples of chemical diversity library chemistries include, peptoids (PCT Publication No. WO 91/019735), encoded peptides (PCT Publication No. WO 93/20242), random bio-oligomers (PCT Publication No. WO 92/00091), benzodiazepines (U.S. Pat. No. 5,288,514), diversomers such as hydantoins, benzodiazepines and dipeptides (Hobbs et al., 1993, Proc. Natl. Acad. Sci. USA, 90:6909-6913), vinylogous polypeptides (Hagihara et al., 1992, J. Amer. Chem. Soc., 114:6568), nonpeptidal peptidomimetics with glucose scaffolding (Hirschmann et al., 1992, J. Amer. Chem. Soc., 114:9217-9218), analogous organic synthesis of small compound libraries (Chen et al., 1994, J. Amer. Chem. Soc., 116:2661), oligocarbamates (Cho et al., 1993, Science, 261:1303), and/or peptidyl phosphonates (Campbell et al., 1994, J. Org. Chem., 59:658), nucleic acid libraries (see Ausubel, Berger and Sambrook, all supra), peptide nucleic acid libraries (U.S. Pat. No. 5,539,083), antibody libraries (e.g., Vaughn et al., 1996, Nature Biotechnology, 14(3):309-314) and PCT/US96/10287), carbohydrate libraries (e.g., Liang et al., 1996, Science, 274-1520-1522) and U.S. Pat. No. 5,593,853), small organic molecule libraries (e.g., benzodiazepines, Baum C&EN, Jan. 18, 1993, page 33; and U.S. Pat. No. 5,288,514; isoprenoids (U.S. Pat. No. 5,569,588); thiazolidinones and metathiazanones (U.S. Pat. No. 5,549,974); pyrrolidines (U.S. Pat. Nos. 5,525,735 and 5,519,134); morpholino compounds (U.S. Pat. No. 5,506,337); and the like.

Devices for the preparation of combinatorial libraries are commercially available (e.g., 357 MPS, 390 MPS, Advanced Chem Tech, Louisville Ky.; Symphony, Rainin, Woburn, Mass.; 433A Applied Biosystems, Foster City, Calif.; 9050 Plus, Millipore, Bedford, Mass.). In addition, a large number of combinatorial libraries are commercially available (e.g., ComGenex, Princeton, N.J.; Asinex, Moscow, Russia; Tripos, Inc., St. Louis, Mo.; ChemStar, Ltd., Moscow, Russia; 3D Pharmaceuticals, Exton, Pa.; Martek Biosciences, Columbia, Md., and the like).

In one aspect, the invention provides solid phase-based in vitro assays in a high throughput format, where the cell or tissue expressing a tyrosine kinase protein/polypeptide/peptide is attached to a solid phase substrate. In such high throughput assays, it is possible to screen up to several thousand different modulators or ligands in a single day. In particular, each well of a microtiter plate can be used to perform a separate assay against a selected potential modulator, or, if concentration or incubation time effects are to be observed, every 5-10 wells can be used to test a single modulator. Thus, a single standard microtiter plate can be used in to assay about 96 modulators. If 1536 well plates are used, then a single plate can easily assay from about 100 to about 1500 different compounds. It is possible to assay several different plates per day; thus, for example, assay screens for up to about 6,000-20,000 different compounds are possible using the described integrated systems.

In another of its aspects, the present invention encompasses screening and small molecule (e.g., drug) detection assays which involve the detection or identification of small molecules that can bind to a given protein, i.e., a tyrosine kinase biomarker polypeptide or peptide, such as a Src tyrosine kinase biomarker polypeptide or peptide. Particularly preferred are assays suitable for high throughput screening methodologies.

In such binding-based detection, identification, or screening assays, a functional assay is not typically required. All that is needed, in general, is a target protein, preferably substantially purified, and a library or panel of compounds (e.g., ligands, drugs, or small molecules), or biological entities to be screened or assayed for binding to the protein target. Preferably, most small molecules that bind to the target protein modulate the target's activity in some manner due to preferential, higher affinity binding to functional areas or sites on the protein.

An example of such an assay is the fluorescence based thermal shift assay (3-Dimensional Pharmaceuticals, Inc., 3DP, Exton, Pa.) as described in U.S. Pat. Nos. 6,020,141 and 6,036,920 to Pantoliano et al. (See also, J. Zimmerman, 2000, Gen. Eng. News, 20(8)). The assay allows the detection of small molecules (e.g., drugs, ligands) that bind to expressed, and preferably purified, tyrosine kinase biomarker proteins/polypeptides/peptides, such as the Src tyrosine kinase, based on affinity of binding determinations by analyzing thermal unfolding curves of protein-drug or ligand complexes. The drugs or binding molecules determined by this technique can be further assayed, if desired, by methods such as those described herein to determine if the molecules affect or modulate function or activity of the target protein.

To purify a tyrosine kinase biomarker polypeptide or peptide, e.g., Src tyrosine kinase, to measure a biological binding or ligand binding activity, the source may be a whole cell lysate that can be prepared by successive freeze-thaw cycles (e.g., one to three) in the presence of standard protease inhibitors. The tyrosine kinase biomarker polypeptide can be partially or completely purified by standard protein purification methods, e.g., affinity chromatography using specific antibody(ies) described herein, or by ligands specific for an epitope tag engineered into the recombinant tyrosine kinase biomarker polypeptide molecule, also as described herein. Binding activity can then be measured as described.

Compounds which are identified according to the methods provided herein, and which modulate or regulate the biological activity or physiology of the tyrosine kinase biomarker polypeptides according to the present invention, are a preferred embodiment of this invention. It is contemplated that such modulatory compounds can be employed in treatment and therapeutic methods for treating a condition that is mediated by the tyrosine kinase biomarker polypeptides, e.g., Src tyrosine kinase biomarker polypeptides, by administering to an individual in need of such treatment a therapeutically effective amount of the compound identified by the methods described herein.

In addition, the present invention provides methods for treating an individual in need of such treatment for a disease, disorder, or condition that is mediated by the tyrosine kinase biomarker polypeptides of the invention, comprising administering to the individual a therapeutically effective amount of the tyrosine kinase biomarker-modulating compound identified by a method provided herein. In accordance with this invention, the tyrosine kinase biomarker polypeptides or proteins encompassed by the methods include members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors.

The present invention particularly provides methods for treating an individual in need of such treatment for a disease, disorder, or condition that is mediated by Src biomarker polypeptides of the invention, comprising administering to the individual a therapeutically effective amount of the Src biomarker-modulating compound identified by a method provided herein.

The present invention further encompasses polypeptides comprising, or alternatively consisting of, an epitope of the polypeptide having an amino acid sequence of one or more of the protein tyrosine kinase biomarkers, preferably the Src biomarker amino acid sequences as set forth in Table 2. The present invention also encompasses polynucleotide sequences encoding an epitope of a polypeptide sequence of the protein tyrosine kinase biomarkers of the invention.

The term “epitopes” as used herein, refers to portions of a polypeptide having antigenic or immunogenic activity in an animal, preferably a mammal, and most preferably a human. In a preferred embodiment, the present invention encompasses a polypeptide comprising an epitope, as well as the polynucleotide encoding this polypeptide. An “immunogenic epitope” as used herein, refers to a portion of a protein that elicits an antibody response in an animal, as determined by any method known in the art, for example, by the methods for generating antibodies described infra. (See, for example, Geysen et al., 1983, Proc. Natl. Acad. Sci. USA, 81:3998-4002). The term “antigenic epitope” as used herein refers to a portion of a protein to which an antibody can immunospecifically bind to its antigen as determined by any method well known in the art, for example, by the immunoassays described herein. Immunospecific binding excludes non-specific binding, but does not necessarily exclude cross-reactivity with other antigens. Antigenic epitopes need not necessarily be immunogenic. Either the full-length protein or an antigenic peptide fragment can be used. Antibodies are preferably prepared from these regions or from discrete fragments in regions of the tyrosine kinase biomarker nucleic acid and protein sequences comprising an epitope. Polypeptide or peptide fragments that function as epitopes may be produced by any conventional means. (See, e.g., Houghten, 1985, Proc. Natl. Acad. Sci. USA, 82:5131-5135; and as described in U.S. Pat. No. 4,631,211).

Moreover, antibodies can also be prepared from any region of the polypeptides and peptides of the protein tyrosine kinase biomarkers, including Src kinase biomarkers as described herein. In addition, if a polypeptide is a receptor protein, antibodies can be developed against an entire receptor or portions of the receptor, for example, the intracellular carboxy terminal domain, the amino terminal extracellular domain, the entire transmembrane domain, specific transmembrane segments, any of the intracellular or extracellular loops, or any portions of these regions. Antibodies can also be developed against specific functional sites, such as the site of ligand binding, or sites that are glycosylated, phosphorylated, myristylated, or amidated, for example.

In the present invention, antigenic epitopes for generating antibodies preferably contain a sequence of at least 4, at least 5, at least 6, at least 7, more preferably at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, and, most preferably, between about 15 to about 30 amino acid residues. Combinations of the foregoing epitopes are included. Preferred polypeptides comprising immunogenic or antigenic epitopes are at least 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 amino acid residues in length. Additional non-exclusive preferred antigenic epitopes include the antigenic epitopes disclosed herein, as well as portions thereof, as well as any combination of two, three, four, five or more of these antigenic epitopes. Such antigenic epitopes can be used as the target molecules in immunoassays. (See, for instance, Wilson et al., 1984, Cell, 37:767-778; and Sutcliffe et al., 1983, Science, 219:660-666). The fragments as described herein are not to be construed, however, as encompassing any fragments which may be disclosed prior to the invention.

Protein tyrosine kinase biomarker polypeptides comprising one or more immunogenic epitopes which elicit an antibody response can be introduced together with a carrier protein, such as an albumin, to an animal system (such as rabbit or mouse). Alternatively, if the polypeptide is of sufficient length (e.g., at least about 15-25 amino acids), the polypeptide can be presented without a carrier. However, immunogenic epitopes comprising as few as 5 to 10 amino acids have been shown to be sufficient to raise antibodies capable of binding to, at the very least, linear epitopes in a denatured polypeptide (e.g., in Western blotting).

Epitope-bearing polypeptides of the present invention can be used to induce antibodies according to methods well known in the art including, but not limited to, in vivo immunization, in vitro immunization, and phage display methods. See, e.g., Sutcliffe et al., supra; Wilson et al., supra; and Bittle et al., supra). If in vivo immunization is used, animals can be immunized with free peptide of appropriate size; however, the anti-peptide antibody titer can be boosted by coupling the peptide to a macromolecular carrier, such as keyhole limpet hemacyanin (KLH), or tetanus toxoid (TT). For instance, peptides containing cysteine residues can be coupled to a carrier using a linker such as maleimidobenzoyl-N-hydroxysuccinimide ester (MBS), while other peptides may be coupled to carriers using a more general linking agent, such as glutaraldehyde.

Peptides containing epitopes can also be synthesized as multiple antigen peptides (MAPs), first described by J. P. Tam et al. (1995, Biomed. Pept., Proteins, Nucleic Acids, 199, 1(3):123-32) and Calvo et al. (1993, J. Immunol., 150(4):1403-12), which are hereby incorporated by reference in their entirety herein. MAPs contain multiple copies of a specific peptide attached to a non-immunogenic lysine core. MAP peptides usually contain four or eight copies of the peptide, which are often referred to as MAP4 or MAP8 peptides. By way of non-limiting example, MAPs can be synthesized onto a lysine core matrix attached to a polyethylene glycol-polystyrene (PEG-PS) support. The peptide of interest is synthesized onto the lysine residues using 9-fluorenylmethoxycarbonyl (Fmoc) chemistry. For example, Applied Biosystems (Foster City, Calif.) offers commercially available MAP resins, such as, for example, the Fmoc Resin 4 Branch and the Fmoc Resin 8 Branch which can be used to synthesize MAPs. Cleavage of MAPs from the resin is performed with standard trifloroacetic acid (TFA)-based cocktails known in the art. Purification of MAPs, except for desalting, is not generally necessary. MAP peptides can be used in immunizing vaccines which elicit antibodies that recognize both the MAP and the native protein from which the peptide was derived.

Epitope-bearing peptides of the invention can also be incorporated into a coat protein of a virus, which can then be used as an immunogen or a vaccine with which to immunize animals, including humans, in order stimulate the production of anti-epitope antibodies. For example, the V3 loop of the gp120 glycoprotein of the human immunodeficiency virus type 1 (HIV-1) has been engineered to be expressed on the surface of rhinovirus. Immunization with rhinovirus displaying the V3 loop peptide yielded apparently effective mimics of the HIV-1 immunogens (as measured by their ability to be neutralized by anti-HIV-1 antibodies as well as by their ability to elicit the production of antibodies capable of neutralizing HIV-1 in cell culture). This techniques of using engineered viral particles as immunogens is described in more detail in Smith et al., 1997, Behring Inst Mitt Feb, (98):229-39; Smith et al., 1998, J. Virol., 72:651-659; and Zhang et al., 1999, Biol. Chem., 380:365-74), which are hereby incorporated by reference herein in their entireties.

Moreover, polypeptides or peptides containing epitopes according to the present invention can be modified, for example, by the addition of amino acids at the amino- and/or carboxy-terminus of the peptide. Such modifications are performed, for example, to alter the conformation of the epitope bearing polypeptide such that the epitope will have a conformation more closely related to the structure of the epitope in the native protein. An example of a modified epitope-bearing polypeptide of the invention is a polypeptide in which one or more cysteine residues have been added to the polypeptide to allow for the formation of a disulfide bond between two cysteines, thus resulting in a stable loop structure of the epitope-bearing polypeptide under non-reducing conditions. Disulfide bonds can form between a cysteine residue added to the polypeptide and a cysteine residue of the naturally-occurring epitope, or between two cysteines which have both been added to the naturally-occurring epitope-bearing polypeptide.

In addition, it is possible to modify one or more amino acid residues of the naturally-occurring epitope-bearing polypeptide by substitution with cysteines to promote the formation of disulfide bonded loop structures. Cyclic thioether molecules of synthetic peptides can be routinely generated using techniques known in the art, e.g., as described in PCT publication WO 97/46251, incorporated in its entirety by reference herein. Other modifications of epitope-bearing polypeptides contemplated by this invention include biotinylation.

For the production of antibodies in vivo, host animals, such as rabbits, rats, mice, sheep, or goats, are immunized with either free or carrier-coupled peptides or MAP peptides, for example, by intraperitoneal and/or intradermal injection. Injection material is typically an emulsion containing about 100 μg of peptide or carrier protein and Freund's adjuvant, or any other adjuvant known for stimulating an immune response. Several booster injections may be needed, for instance, at intervals of about two weeks, to provide a useful titer of anti-peptide antibody which can be detected, for example, by ELISA assay using free peptide adsorbed to a solid surface. The titer of anti-peptide antibodies in serum from an immunized animal can be increased by selection of anti-peptide antibodies, e.g., by adsorption of the peptide onto a solid support and elution of the selected antibodies according to methods well known in the art.

As one having skill in the art will appreciate, and as discussed above, the tyrosine kinase biomarker polypeptides of the present invention, which include the following: e.g., members of the Src family of tyrosine kinases, such as Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors, and which comprise an immunogenic or antigenic epitope, can be fused to other polypeptide sequences. For example, the polypeptides of the present invention can be fused with the constant domain of immunoglobulins (IgA, IgE, IgG, IgD, or IgM), or portions thereof, e.g., CH1, CH2, CH3, or any combination thereof, and portions thereof, or with albumin (including, but not limited to, recombinant human albumin, or fragments or variants thereof (see, e.g., U.S. Pat. No. 5,876,969; EP Patent No. 0 413 622; and U.S. Pat. No. 5,766,883, incorporated by reference in their entirety herein), thereby resulting in chimeric polypeptides. Such fusion proteins may facilitate purification and may increase half-life in vivo. This has been shown for chimeric proteins containing the first two domains of the human CD4-polypeptide and various domains of the constant regions of the heavy or light chains of mammalian immunoglobulins. (see, e.g., Traunecker et al., 1988, Nature, 331:84-86).

Enhanced delivery of an antigen across the epithelial barrier to the immune system has been demonstrated for antigens (e.g., insulin) conjugated to an FcRn binding partner, such as IgG or Fc fragments (see, e.g., WO 96/22024 and WO 99/04813). IgG fusion proteins that have a disulfide-linked dimeric structure due to the IgG portion disulfide bonds have also been found to be more efficient in binding and neutralizing other molecules than are monomeric polypeptides, or fragments thereof, alone. (See, e.g., Fountoulakis et al., 1995, J. Biochem., 270:3958-3964).

Nucleic acids encoding epitopes can also be recombined with a polynucleotide of interest as an epitope tag (e.g., the hemagglutinin (“HA”) tag or flag tag) to aid in detection and purification of the expressed polypeptide. For example, a system for the ready purification of non-denatured fusion proteins expressed in human cell lines has been described by Janknecht et al., (1991, Proc. Natl. Acad. Sci. USA, 88:8972-897). In this system, the polynucleotide of interest is subcloned into a vaccinia recombination plasmid such that the open reading frame of the polynucleotide is translationally fused to an amino-terminal tag having six histidine residues. The tag serves as a matrix binding domain for the fusion protein. Extracts from cells infected with the recombinant vaccinia virus are loaded onto an Ni²⁺ nitriloacetic acid-agarose column and histidine-tagged proteins are selectively eluted with imidazole-containing buffers.

Additional fusion proteins of the invention can be generated by employing the techniques of gene-shuffling, motif-shuffling, exon-shuffling, and/or codon-shuffling (collectively referred to as “DNA shuffling”). DNA shuffling can be employed to modulate the activities of polypeptides of the invention; such methods can be used to generate polypeptides with altered activity, as well as agonists and antagonists of the polypeptides. See, generally, U.S. Pat. Nos. 5,605,793; 5,811,238; 5,830,721; 5,834,252; and 5,837,458, and Patten et al., 1997, Curr. Opinion Biotechnol., 8:724-33; Harayama, 1998, Trends Biotechnol., 16(2):76-82; Hansson, et al., 1999, J. Mol. Biol., 287:265-76; and Lorenzo and Blasco, 1998, Biotechniques, 24(2):308-313, the contents of each of which are hereby incorporated by reference in its entirety.

In an embodiment of the invention, alteration of polynucleotides corresponding to one or more of the src biomarker polynucleotide sequences as set forth in Table 2, and the polypeptides encoded by these polynucleotides, can be achieved by DNA shuffling. DNA shuffling involves the assembly of two or more DNA segments by homologous or site-specific recombination to generate variation in the polynucleotide sequence. In another embodiment, polynucleotides of the invention, or their encoded polypeptides, may be altered by being subjected to random mutapolynucleotidesis by error-prone PCR, random nucleotide insertion, or other methods, prior to recombination. In another embodiment, one or more components, motifs, sections, parts, domains, fragments, etc., of a polynucleotide encoding a polypeptide of this invention may be recombined with one or more components, motifs, sections, parts, domains, fragments, etc. of one or more heterologous molecules.

Another aspect of the present invention relates to antibodies and T-cell antigen receptors (TCRs), which immunospecifically bind to a polypeptide, polypeptide fragment, or variant one or more of the src biomarker amino acid sequences as set forth in Table 2, and/or an epitope thereof, of the present invention (as determined by immunoassays well known in the art for assaying specific antibody-antigen binding).

A bispecific or bifunctional antibody is an artificial hybrid antibody having two different heavy/light chain pairs and two different binding sites. Bispecific antibodies can be produced by a variety of methods, including fusion of hybridomas or linking of Fab′ fragments. (See, e.g., Songsivilai & Lachmann, 1990, Clin. Exp. Immunol., 79:315-321; Kostelny et al., 1992, J. Immunol., 148:1547 1553). In addition, bispecific antibodies can be formed as “diabodies” (See, Holliger et al., 1993, Proc. Natl. Acad. Sci. USA, 90:6444-6448), or “Janusins” (See, Traunecker et al., 1991, EMBO J., 10:3655-3659 and Traunecker et al., 1992, Int. J. Cancer Suppl. 7:51-52-127).

Antibodies of the invention include, but are not limited to, polyclonal, monoclonal, multispecific, human, humanized or chimeric antibodies, single chain antibodies, Fab fragments, F(ab′) fragments, fragments produced by a Fab expression library, anti-idiotypic (anti-Id) antibodies (including, e.g., anti-Id antibodies to antibodies of the invention), intracellularly made antibodies (i.e., intrabodies), and epitope-binding fragments of any of the above. The term “antibody”, as used herein, refers to immunoglobulin molecules and immunologically active portions or fragments of immunoglobulin molecules, i.e., molecules that contain an antigen binding site that immunospecifically binds an antigen. The immunoglobulin molecules of the invention can be of any type (e.g., IgG, IgE, IgM, IgD, IgA and IgY), class or subclass (e.g., IgG1, IgG2, IgG3, IgG4, IgA1 and IgA2) of immunoglobulin molecule. Preferably, immunoglobulin is an IgG1, an IgG2, or an IgG4 isotype.

Immunoglobulins may have both a heavy and a light chain. An array of IgG, IgE, IgM, IgD, IgA, and IgY heavy chains can be paired with a light chain of the kappa or lambda types. Most preferably, the antibodies of the present invention are human antigen-binding antibodies and antibody fragments and include, but are not limited to, Fab, Fab′ F(ab′) 2, Fd, single-chain Fvs (scFv), single-chain antibodies, disulfide-linked Fvs (sdFv) and fragments comprising either a V_(L) or V_(H) domain. Antigen-binding antibody fragments, including single-chain antibodies, can comprise the variable region(s) alone or in combination with the entirety or a portion of the following: hinge region, and CH1, CH2, and CH3 domains. Also included in connection with the invention are antigen-binding fragments comprising any combination of variable region(s) with a hinge region, and CH1, CH2, and CH3 domains. The antibodies of the invention can be from any animal origin including birds and mammals. Preferably, the antibodies are of human, murine (e.g., mouse and rat), donkey, sheep, rabbit, goat, guinea pig, camel, horse, or chicken origin. As used herein, “human” antibodies include antibodies having the amino acid sequence of a human immunoglobulin and include antibodies isolated from human immunoglobulin libraries or from animals transgenic for one or more human immunoglobulin and that do not express endogenous immunoglobulins, as described infra and, for example, in U.S. Pat. No. 5,939,598.

The antibodies of the present invention can be monospecific, bispecific, trispecific, or of greater multispecificity. Multispecific antibodies can be specific for different epitopes of a polypeptide of the present invention, or can be specific for both a polypeptide of the present invention, and a heterologous epitope, such as a heterologous polypeptide or solid support material. (See, e.g., WO 93/17715; WO 92/08802; WO 91/00360; WO 92/05793; Tutt et al., 1991, J. Immunol., 147:60-69; U.S. Pat. Nos. 4,474,893; 4,714,681; 4,925,648; 5,573,920; 5,601,819; and Kostelny et al., 1992, J. Immunol., 148:1547-1553).

Antibodies of the present invention can be described or specified in terms of the epitope(s) or portion(s) of a polypeptide of the present invention which they recognize or specifically bind. The epitope(s) or polypeptide portion(s) can be specified, e.g., by N-terminal and C-terminal positions, by size in contiguous amino acid residues, or as presented in the sequences defined in Table 2 herein. Further included in accordance with the present invention are antibodies which bind to polypeptides encoded by polynucleotides which hybridize to a polynucleotide of the present invention under stringent, or moderately stringent, hybridization conditions as described herein.

The antibodies of the invention (including molecules comprising, or alternatively consisting of, antibody fragments or variants thereof) can bind immunospecifically to a polypeptide or polypeptide fragment or to a variant human protein tyrosine kinase biomarker of the invention, e.g., the Src biomarker proteins as set forth in Table 2, and/or monkey src biomarker protein.

By way of non-limiting example, an antibody can be considered to bind to a first antigen preferentially if it binds to the first antigen with a dissociation constant (Kd) that is less than the antibody's Kd for the second antigen. In another non-limiting embodiment, an antibody can be considered to bind to a first antigen preferentially if it binds to the first antigen with an affinity that is at least one order of magnitude less than the antibody's Ka for the second antigen. In another non-limiting embodiment, an antibody can be considered to bind to a first antigen preferentially if it binds to the first antigen with an affinity that is at least two orders of magnitude less than the antibody's Kd for the second antigen.

In another nonlimiting embodiment, an antibody may be considered to bind to a first antigen preferentially if it binds to the first antigen with an off rate (koff) that is less than the antibody's koff for the second antigen. In another nonlimiting embodiment, an antibody can be considered to bind to a first antigen preferentially if it binds to the first antigen with an affinity that is at least one order of magnitude less than the antibody's koff for the second antigen. In another nonlimiting embodiment, an antibody can be considered to bind to a first antigen preferentially if it binds to the first antigen with an affinity that is at least two orders of magnitude less than the antibody's koff for the second antigen.

Antibodies of the present invention can also be described or specified in terms of their binding affinity to a tyrosine kinase biomarker polypeptide of the present invention, e.g., members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors. Preferred binding affinities include those with a dissociation constant or Kd of less than 5×10⁻² M, 1×10⁻² M, 5×10⁻³ M, 1×10⁻³ M, 5×10⁻⁴ M, or 1×10⁻⁴ M. More preferred binding affinities include those with a dissociation constant or Kd less than 5×10⁻⁵ M, 1×10⁻⁵ M, 5×10⁻⁶ M, 1×10⁻⁶ M, 5×10⁻⁷ M, 1×10⁻⁷ M, 5×10⁻⁸ M, or 1×10⁻⁸ M. Even more preferred antibody binding affinities include those with a dissociation constant or Kd of less than 5×10⁻⁹ M, 1×10⁻⁹ M, 5×10⁻¹⁰ M, 1×10⁻¹⁰ M, 5×10⁻¹¹ M, 1×10⁻¹¹ M, 5×10⁻¹² M, 1×10⁻¹² M, 5×10⁻¹³ M, 1×10⁻¹³ M, 5×10⁻¹⁴ M, 1×10⁻¹⁴ M, 5×10⁻¹⁵ M, or 1×10⁻¹⁵ M.

In specific embodiments, antibodies of the invention bind to the protein tyrosine kinase biomarker polypeptides, or fragments, or variants thereof, with an off rate (koff) of less than or equal to about 5×10⁻² sec⁻¹, 1×10⁻² sec⁻¹, 5×10⁻³ sec⁻¹, or 1×10⁻³ sec⁻¹. More preferably, antibodies of the invention bind to src biomarker protein polypeptides or fragments or variants thereof with an off rate (koff) of less than or equal to about 5×10⁻⁴ sec⁻¹, 1×10⁻⁴ sec⁻¹, 5×10⁻⁵ sec⁻¹, 1×10⁻⁵ sec⁻¹, 5×10⁻⁶ sec⁻¹, 1×10⁻⁶ sec⁻¹, 5×10⁻⁷ sec⁻¹, or 1×10⁻⁷ sec⁻¹.

In other embodiments, antibodies of the invention bind to protein tyrosine kinase biomarker polypeptides or fragments or variants thereof with an on rate (kon) of greater than or equal to 1×10³ M⁻¹ sec⁻¹, 5×10³ M⁻¹ sec⁻¹, 1×10⁴ M⁻¹ sec⁻¹, or 5×10⁴ M⁻¹ sec⁻¹. More preferably, antibodies of the invention bind to protein tyrosine kinase biomarker polypeptides or fragments or variants thereof with an on rate greater than or equal to 1×10⁵ M⁻¹ sec⁻¹, 5×10⁵ M⁻¹ sec⁻¹, 1×10⁶ M⁻¹ sec−1, 5×10⁻⁶ M⁻¹ sec⁻¹, or 1×10⁻⁷ M⁻¹ sec⁻¹.

The present invention also provides antibodies that competitively inhibit the binding of an antibody to an epitope of the invention as determined by any method known in the art for determining competitive binding, for example, the immunoassays as described herein. In preferred embodiments, the antibody competitively inhibits binding to an epitope by at least 95%, at least 90%, at least 85%, at least 80%, at least 75%, at least 70%, at least 60%, or at least 50%.

Antibodies of the present invention can act as agonists or antagonists of the protein tyrosine kinase biomarker polypeptides of the present invention. For example, the present invention includes antibodies which disrupt receptor/ligand interactions with polypeptides of the invention either partially or fully. The invention includes both receptor-specific antibodies and ligand-specific antibodies. The invention also includes receptor-specific antibodies which do not prevent ligand binding, but do prevent receptor activation. Receptor activation (i.e., signaling) can be determined by techniques described herein or as otherwise known in the art. For example, receptor activation can be determined by detecting the phosphorylation (e.g., on tyrosine or serine/threonine) of the receptor or its substrate by immunoprecipitation followed by Western Blot analysis. In specific embodiments, antibodies are provided that inhibit ligand activity or receptor activity by at least 95%, at least 90%, at least 85%, at least 80%, at least 75%, at least 70%, at least 60%, or at least 50% of the activity in the absence of the antibody.

In another embodiment of the present invention, antibodies that immunospecifically bind to a protein tyrosine kinase biomarker, or a fragment or variant thereof, comprise a polypeptide having the amino acid sequence of any one of the heavy chains expressed by an anti-protein tyrosine kinase biomarker antibody-expressing cell line of the invention, and/or any one of the light chains expressed by an anti-protein tyrosine kinase biomarker antibody-expressing cell line of the invention.

In another embodiment of the present invention, antibodies that immunospecifically bind to a tyrosine kinase biomarker protein or a fragment or variant thereof, comprise a polypeptide having the amino acid sequence of any one of the V_(H) domains of a heavy chain expressed by an anti-protein tyrosine kinase biomarker antibody-expressing cell line, and/or any one of the V_(L) domains of a light chain expressed by an anti-protein tyrosine kinase biomarker antibody-expressing cell line. In preferred embodiments, antibodies of the present invention comprise the amino acid sequence of a V_(H) domain and V_(L) domain expressed by a single anti-protein tyrosine kinase biomarker protein antibody-expressing cell line. In alternative embodiments, antibodies of the present invention comprise the amino acid sequence of a V_(H) domain and a V_(L) domain expressed by two different anti-protein tyrosine kinase biomarker antibody-expressing cell lines.

Molecules comprising, or alternatively consisting of, antibody fragments or variants of the V_(H) and/or V_(L) domains expressed by an anti-protein tyrosine kinase biomarker antibody-expressing cell line that immunospecifically bind to a tyrosine kinase biomarker protein, e.g., Src tyrosine kinase, are also encompassed by the invention, as are nucleic acid molecules encoding these V_(H) and V_(L) domains, molecules, fragments and/or variants.

The present invention also provides antibodies that immunospecificially bind to a polypeptide, or polypeptide fragment or variant of a tyrosine kinase biomarker protein, e.g., a Src kinase biomarker protein, wherein such antibodies comprise, or alternatively consist of, a polypeptide having an amino acid sequence of any one, two, three, or more of the V_(H) CDRs contained in a heavy chain expressed by one or more anti-tyrosine kinase biomarker protein antibody expressing cell lines. In particular, the invention provides antibodies that immunospecifically bind to a tyrosine kinase biomarker protein, comprising, or alternatively consisting of, a polypeptide having the amino acid sequence of a V_(H) CDR1 contained in a heavy chain expressed by one or more anti-tyrosine kinase biomarker protein antibody expressing cell lines. In another embodiment, antibodies that immunospecifically bind to a tyrosine kinase biomarker protein, comprise, or alternatively consist of, a polypeptide having the amino acid sequence of a V_(H) CDR2 contained in a heavy chain expressed by one or more anti-tyrosine kinase biomarker protein antibody expressing cell lines. In a preferred embodiment, antibodies that immunospecifically bind to a tyrosine kinase biomarker protein, comprise, or alternatively consist of, a polypeptide having the amino acid sequence of a V_(H) CDR3 contained in a heavy chain expressed by one or more anti-tyrosine kinase biomarker protein antibody expressing cell line of the invention. Molecules comprising, or alternatively consisting of, these antibodies or antibody fragments or variants thereof that immunospecifically bind to a tyrosine kinase biomarker protein or a tyrosine kinase biomarker protein fragment or variant thereof are also encompassed by the invention, as are nucleic acid molecules encoding these antibodies, molecules, fragments and/or variants.

The present invention also provides antibodies that immunospecificially bind to a polypeptide, or polypeptide fragment or variant of a tyrosine kinase biomarker protein, e.g., a Src kinase biomarker protein, wherein the antibodies comprise, or alternatively consist of, a polypeptide having an amino acid sequence of any one, two, three, or more of the V_(L) CDRs contained in a heavy chain expressed by one or more anti-tyrosine kinase biomarker protein antibody expressing cell lines of the invention. In particular, the invention provides antibodies that immunospecifically bind to a tyrosine kinase biomarker protein, comprising, or alternatively consisting of, a polypeptide having the amino acid sequence of a V_(L) CDR1 contained in a heavy chain expressed by one or more anti-tyrosine kinase biomarker protein antibody-expressing cell lines of the invention. In another embodiment, antibodies that immunospecifically bind to a src biomarker protein, comprise, or alternatively consist of, a polypeptide having the amino acid sequence of a V_(L) CDR2 contained in a heavy chain expressed by one or more anti-tyrosine kinase biomarker protein antibody-expressing cell lines of the invention. In a preferred embodiment, antibodies that immunospecifically bind to a tyrosine kinase biomarker protein, comprise, or alternatively consist of, a polypeptide having the amino acid sequence of a V_(L) CDR3 contained in a heavy chain expressed by one or more anti-tyrosine kinase biomarker protein antibody-expressing cell lines of the invention. Molecules comprising, or alternatively consisting of, these antibodies, or antibody fragments or variants thereof, that immunospecifically bind to a tyrosine kinase biomarker protein or a tyrosine kinase biomarker protein fragment or variant thereof are also encompassed by the invention, as are nucleic acid molecules encoding these antibodies, molecules, fragments and/or variants.

The present invention also provides antibodies (including molecules comprising, or alternatively consisting of, antibody fragments or variants) that immunospecifically bind to a tyrosine kinase biomarker protein, polypeptide or polypeptide fragment or variant of a tyrosine kinase biomarker protein, e.g., Src tyrosine kinase, wherein the antibodies comprise, or alternatively consist of, one, two, three, or more V_(H) CDRs, and one, two, three or more V_(L) CDRs, as contained in a heavy chain or light chain expressed by one or more anti-tyrosine kinase biomarker protein antibody-expressing cell lines of the invention. In particular, the invention provides antibodies that immunospecifically bind to a polypeptide or polypeptide fragment or variant of a tyrosine kinase biomarker protein, wherein the antibodies comprise, or alternatively consist of, a V_(H) CDR1 and a V_(L) CDR1, a V_(H) CDR1 and a V_(L) CDR2, a V_(H) CDR1 and a V_(L) CDR3, a V_(H) CDR2 and a V_(L) CDR1, VH CDR2 and V_(L) CDR2, a V_(H) CDR2 and a V_(L) CDR3, a V_(H) CDR3 and a V_(H) CDR1, a V_(H) CDR3 and a V_(L) CDR2, a V_(H) CDR3 and a V_(L) CDR3, or any combination thereof, of the V_(H) CDRs and V_(L) CDRs contained in a heavy chain or light chain immunoglobulin molecule expressed by one or more anti-tyrosine kinase biomarker protein antibody-expressing cell lines of the invention. In a preferred embodiment, one or more of these combinations are from a single anti-tyrosine kinase biomarker protein antibody-expressing cell line of the invention. Molecules comprising, or alternatively consisting of, fragments or variants of these antibodies that immunospecifically bind to the tyrosine kinase biomarker proteins are also encompassed by the invention, as are nucleic acid molecules encoding these antibodies, molecules, fragments or variants.

The present invention also provides nucleic acid molecules, generally isolated, encoding an antibody of the invention (including molecules comprising, or alternatively consisting of, antibody fragments or variants thereof). In a specific embodiment, a nucleic acid molecule of the invention encodes an antibody (including molecules comprising, or alternatively consisting of, antibody fragments or variants thereof), comprising, or alternatively consisting of, a V_(H) domain having an amino acid sequence of any one of the V_(H) domains of a heavy chain expressed by an anti-tyrosine kinase biomarker protein antibody-expressing cell line of the invention and a V_(L) domain having an amino acid sequence of a light chain expressed by an anti-tyrosine kinase biomarker protein antibody-expressing cell line of the invention. In another embodiment, a nucleic acid molecule of the invention encodes an antibody (including molecules comprising, or alternatively consisting of, antibody fragments or variants thereof), comprising, or alternatively consisting of, a V_(H) domain having an amino acid sequence of any one of the V_(H) domains of a heavy chain expressed by an anti-tyrosine kinase biomarker protein antibody-expressing cell line of the invention, or a V_(L) domain having an amino acid sequence of a light chain expressed by an anti-tyrosine kinase biomarker protein antibody-expressing cell line of the invention.

The present invention also provides antibodies that comprise, or alternatively consist of, variants (including derivatives) of the antibody molecules (e.g., the V_(H) domains and/or V_(L) domains) described herein, which antibodies immunospecifically bind to a tyrosine kinase biomarker protein or fragment or variant thereof, e.g., a Src tyrosine kinase polypeptide.

Standard techniques known to those of skill in the art can be used to introduce mutations in the nucleotide sequence encoding a molecule of the invention, including, for example, site-directed mutapolynucleotidesis and PCR-mediated mutapolynucleotidesis which result in amino acid substitutions. Preferably the molecules are immunoglobulin molecules. Also preferably, the variants (including derivatives) encode less than 50 amino acid substitutions, less than 40 amino acid substitutions, less than 30 amino acid substitutions, less than 25 amino acid substitutions, less than 20 amino acid substitutions, less than 15 amino acid substitutions, less than 10 amino acid substitutions, less than 5 amino acid substitutions, less than 4 amino acid substitutions, less than 3 amino acid substitutions, or less than 2 amino acid substitutions, relative to the reference V_(H) domain, V_(H) CDR1, V_(H) CDR2, V_(H) CDR3, V_(L) domain, V_(L) CDR1, V_(L) CDR2, or V_(L) CDR3.

A “conservative amino acid substitution” is one in which the amino acid residue is replaced with an amino acid residue having a side chain with a similar charge. Families of amino acid residues having side chains with similar charges have been defined in the art. These families include amino acids with basic side chains (e.g., lysine, arginine, histidine), acidic side chains (e.g., aspartic acid, glutamic acid), uncharged polar side chains (e.g., glycine, asparagine, glutamine, serine, threonine, tyrosine, cysteine), nonpolar side chains (e.g., alanine, valine, leucine, isoleucine, proline, phenylalanine, methionine, tryptophan), beta-branched side chains (e.g., threonine, valine, isoleucine) and aromatic side chains (e.g., tyrosine, phenylalanine, tryptophan, histidine). Alternatively, mutations can be introduced randomly along all or part of the coding sequence, such as by saturation mutapolynucleotidesis. The resultant mutants can be screened for biological activity to identify mutants that retain activity.

For example, it is possible to introduce mutations only in framework regions or only in CDR regions of an antibody molecule. Introduced mutations can be silent or neutral missense mutations, i.e., have no, or little, effect on an antibody's ability to bind antigen. These types of mutations can be useful to optimize codon usage, or to improve hybridoma antibody production. Alternatively, non-neutral missense mutations can alter an antibody's ability to bind antigen. The location of most silent and neutral missense mutations is likely to be in the framework regions, while the location of most non-neutral missense mutations is likely to be in the CDRs, although this is not an absolute requirement. One of skill in the art is able to design and test mutant molecules with desired properties, such as no alteration in antigen binding activity or alteration in binding activity (e.g., improvements in antigen binding activity or change in antibody specificity). Following mutapolynucleotidesis, the encoded protein may routinely be expressed and the functional and/or biological activity of the encoded protein can be determined using techniques described herein or by routinely modifying techniques known and practiced in the art.

In a specific embodiment, an antibody of the invention (including a molecule comprising, or alternatively consisting of, an antibody fragment or variant thereof), that immunospecifically binds to protein tyrosine kinase biomarker polypeptides or fragments or variants thereof, comprises, or alternatively consists of, an amino acid sequence encoded by a nucleotide sequence that hybridizes to a nucleotide sequence that is complementary to that encoding one of the V_(H) or V_(L) domains expressed by one or more anti-tyrosine kinase biomarker protein antibody-expressing cell lines of the invention, preferably under stringent conditions, e.g., hybridization to filter-bound DNA in 6× sodium chloride/sodium citrate (SSC) at about 45° C. followed by one or more washes in 0.2×SSC/0.1% SDS at about 50° C. -65° C., preferably under highly stringent conditions, e.g., hybridization to filter-bound nucleic acid in 6×SSC at about 45° C. followed by one or more washes in 0.1×SSC/0.2% SDS at about 68° C., or under other stringent hybridization conditions which are known to those of skill in the art (see, for example, Ausubel, F. M. et al., eds., 1989, Current Protocols in Molecular Biology, Vol. I, Green Publishing Associates, Inc. and John Wiley & Sons, Inc., New York at pages 6.3.1-6.3.6 and 2.10.3). Nucleic acid molecules encoding these antibodies are also encompassed by the invention.

It is well known within the art that polypeptides, or fragments or variants thereof, with similar amino acid sequences often have similar structure and many of the same biological activities. Thus, in one embodiment, an antibody (including a molecule comprising, or alternatively consisting of, an antibody fragment or variant thereof), that immunospecifically binds to a protein tyrosine kinase biomarker polypeptide or fragments or variants of a tyrosine kinase biomarker polypeptide, comprises, or alternatively consists of, a V_(H) domain having an amino acid sequence that is at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, or at least 99% identical to the amino acid sequence of a V_(H) domain of a heavy chain expressed by an anti-tyrosine kinase biomarker protein antibody-expressing cell line of the invention.

In another embodiment, an antibody (including a molecule comprising, or alternatively consisting of, an antibody fragment or variant thereof), that immunospecifically binds to a tyrosine kinase biomarker polypeptide, or fragments or variants of a tyrosine kinase biomarker protein polypeptide, comprises, or alternatively consists of, a V_(L) domain having an amino acid sequence that is at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, or at least 99% identical to the amino acid sequence of a V_(L) domain of a light chain expressed by an anti-tyrosine kinase biomarker protein antibody-expressing cell line of the invention.

The present invention also provides antibodies (including molecules comprising, or alternatively consisting of, antibody fragments or variants thereof), that down-regulate the cell-surface expression of a tyrosine kinase biomarker protein, as determined by any method known in the art such as, for example, FACS analysis or immunofluorescence assays. By way of a non-limiting hypothesis, such down-regulation can be the result of antibody-induced internalization of a tyrosine kinase biomarker protein. Such antibodies can comprise, or alternatively consist of, a portion (e.g., V_(H) CDR1, V_(H) CDR2, V_(H) CDR3, V_(L) CDR1, V_(L) CDR2, or V_(L) CDR3) of a V_(H) or V_(L) domain having an amino acid sequence of an antibody of the invention, or a fragment or variant thereof.

In another embodiment, an antibody that down-regulates the cell-surface expression of a tyrosine kinase biomarker protein comprises, or alternatively consists of, a polypeptide having the amino acid sequence of a V_(H) domain of an antibody of the invention, or a fragment or variant thereof and a V_(L) domain of an antibody of the invention, or a fragment or variant thereof. In another embodiment, an antibody that down-regulates the cell-surface expression of a tyrosine kinase biomarker protein comprises, or alternatively consists of, a polypeptide having the amino acid sequence of a V_(H) domain and a V_(L) domain from a single antibody (or scFv or Fab fragment) of the invention, or fragments or variants thereof. In another embodiment, an antibody that down-regulates the cell-surface expression of a tyrosine kinase biomarker protein comprises, or alternatively consists of, a polypeptide having the amino acid sequence of a V_(H) domain of an antibody of the invention, or a fragment or variant thereof. In another embodiment, an antibody that down-regulates the cell-surface expression of a tyrosine kinase biomarker protein comprises, or alternatively consists of, a polypeptide having the amino acid sequence of a V_(L) domain of an antibody of the invention, or a fragment or variant thereof.

In a preferred embodiment, an antibody that down-regulates the cell-surface expression of a tyrosine kinase biomarker protein comprises, or alternatively consists of, a polypeptide having the amino acid sequence of a V_(H) CDR3 of an antibody of the invention, or a fragment or variant thereof. In another preferred embodiment, an antibody that down-regulates the cell-surface expression of a tyrosine kinase biomarker protein comprises, or alternatively consists of, a polypeptide having the amino acid sequence of a V_(L) CDR3 of an antibody of the invention, or a fragment or variant thereof. Nucleic acid molecules encoding these antibodies are also encompassed by the invention.

In another preferred embodiment, an antibody that enhances the activity of a tyrosine kinase biomarker protein, or a fragment or variant thereof, comprises, or alternatively consists of, a polypeptide having the amino acid sequence of a V_(L) CDR3 of an antibody of the invention, or a fragment or variant thereof. Nucleic acid molecules encoding these antibodies are also encompassed by the invention.

As nonlimiting examples, antibodies of the present invention can be used to purify, detect, and target the protein tyrosine kinase polypeptides of the present invention, including both in vitro and in vivo diagnostic, detection, screening, and/or therapeutic methods. For example, the antibodies have been used in immunoassays for qualitatively and quantitatively measuring levels of src biomarker polypeptides in biological samples. (See, e.g., Harlow et al., Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, 2nd Ed. 1988, which is incorporated by reference herein in its entirety).

By way of another nonlimiting example, antibodies of the invention can be administered to individuals as a form of passive immunization. Alternatively, antibodies of the present invention can be used for epitope mapping to identify the epitope(s) that are bound by the antibody. Epitopes identified in this way can, in turn, for example, be used as vaccine candidates, i.e., to immunize an individual to elicit antibodies against the naturally-occurring forms of one or more tyrosine kinase biomarker proteins.

As discussed in more detail below, the antibodies of the present invention can be used either alone or in combination with other compositions. The antibodies can further be recombinantly fused to a heterologous polypeptide at the N- or C-terminus, or chemically conjugated (including covalent and non-covalent conjugations) to polypeptides or other compositions. For example, antibodies of the present invention can be recombinantly fused or conjugated to molecules that are useful as labels in detection assays and to effector molecules such as heterologous polypeptides, drugs, radionuclides, or toxins. See, e.g., PCT publications WO 92/08495; WO 91/14438; WO 89/12624; U.S. Pat. No. 5,314,995 and EP 396, 387.

The antibodies of the invention include derivatives that are modified, i.e., by the covalent attachment of any type of molecule to the antibody. For example, without limitation, the antibody derivatives include antibodies that have been modified, e.g., by glycosylation, acetylation, pegylation, phosphorylation, amidation, derivatization by known protecting/blocking groups, proteolytic cleavage, linkage to a cellular ligand or other protein, etc. Any of numerous chemical modifications can be carried out by known techniques, including, but not limited to, specific chemical cleavage, acetylation, formylation, metabolic synthesis of tunicamycin, and the like. In addition, the antibody derivative can contain one or more non-classical amino acids.

The antibodies of the present invention can be generated by any suitable method known in the art. Polyclonal antibodies directed against an antigen or immunogen of interest can be produced by various procedures well known in the art. For example, a tyrosine kinase biomarker polypeptide or peptide of the invention can be administered to various host animals as elucidated above to induce the production of sera containing polyclonal antibodies specific for the biomarker antigen. Various adjuvants can also be used to increase the immunological response, depending on the host species; adjuvants include, but are not limited to, Freund's (complete and incomplete), mineral gels such as aluminum hydroxide, surface active substances such as lysolecithin, pluronic polyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyanins, dinitrophenol, and potentially useful human adjuvants such as BCG (bacille Calmette-Guerin) and corynebacterium parvum. Such adjuvants are also well known in the art.

Monoclonal antibodies can be prepared using a wide variety of techniques known in the art, including the use of hybridoma, recombinant and phage display technologies, or a combination thereof. For example, monoclonal antibodies can be produced using hybridoma techniques as known and practiced in the art and as taught, for example, in Kohler and Milstein, 1975, Nature, 256:495-497; Harlow et al., Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, 2nd Ed. 1988; and Hammerling, et al., In: Monoclonal Antibodies and T-Cell Hybridomas, Elsevier, N.Y., pages 563-681, 1981, the contents of which are incorporated herein by reference in their entireties. The term “monoclonal antibody” as used herein is not limited to antibodies produced through hybridoma technology. The term “monoclonal antibody” refers to an antibody that is derived from a single clone, including any eukaryotic, prokaryotic, or phage clone, and does not necessarily refer to the method by which it is produced. Techniques involving continuous cell line cultures can also be used. In addition to the hybridoma technique, other techniques include the trioma technique, the human B-cell hybridoma technique (Kozbor et al., 1983, Immunol. Today, 4:72), and the EBV-hybridoma technique (Cole et al., 1985. In: Monoclonal Antibodies and Cancer Therapy, Alan R. Liss, Inc., pp. 77-96).

Methods for producing and screening for specific antibodies using hybridoma technology are routine and well known in the art. As a nonlimiting example, mice can be immunized with a tyrosine kinase polypeptide or peptide of the invention, or variant thereof, or with a cell expressing the polypeptide or peptide or variant thereof. Once an immune response is detected, e.g., antibodies specific for the antigen are detected in the sera of immunized mice, the spleen is harvested and splenocytes are isolated. The splenocytes are then fused by well known techniques to any suitable myeloma cells, for example cells from cell line SP2/0 or P3X63-AG8.653 available from the ATCC. Hybridomas are selected and cloned by limiting dilution techniques. The hybridoma clones are then assayed by methods known in the art to determine and select those cells that secrete antibodies capable of binding to a polypeptide of the invention. Ascites fluid, which generally contains high levels of antibodies, can be generated by immunizing mice with positive hybridoma clones.

Another well known method for producing both polyclonal and monoclonal human B cell lines is transformation using Epstein Barr Virus (EBV). Protocols for generating EBV-transformed B cell lines are commonly known in the art, such as, for example, the protocol outlined in Chapter 7.22 of Current Protocols in Immunology, Coligan et al., Eds., 1994, John Wiley & Sons, NY, which is hereby incorporated by reference herein in its entirety. The source of B cells for transformation is commonly human peripheral blood, but B cells for transformation can also be obtained from other sources including, but not limited to, lymph node, tonsil, spleen, tumor tissue, and infected tissues. Tissues are generally prepared as single cell suspensions prior to EBV transformation. In addition, T cells that may be present in the B cell samples can be either physically removed or inactivated (e.g., by treatment with cyclosporin A). The removal of T cells is often advantageous, because T cells from individuals seropositive for anti-EBV antibodies can suppress B cell immortalization by EBV. In general, a sample containing human B cells is innoculated with EBV and cultured for 3-4 weeks. A typical source of EBV is the culture supernatant of the B95-8 cell line (ATCC; VR-1492). Physical signs of EBV transformation can generally be seen toward the end of the 3-4 week culture period.

By phase-contrast microscopy, transformed cells appear large, clear and “hairy”; they tend to aggregate in tight clusters of cells. Initially, EBV lines are generally polyclonal. However, over prolonged periods of cell culture, EBV lines can become monoclonal as a result of the selective outgrowth of particular B cell clones. Alternatively, polyclonal EBV transformed lines can be subcloned (e.g., by limiting dilution) or fused with a suitable fusion partner and plated at limiting dilution to obtain monoclonal B cell lines. Suitable fusion partners for EBV transformed cell lines include mouse myeloma cell lines (e.g., SP2/0, X63-Ag8.653), heteromyeloma cell lines (human×mouse; e.g., SPAM-8, SBC-H20, and CB-F7), and human cell lines (e.g., GM 1500, SKO-007, RPMI 8226, and KR-4). Thus, the present invention also includes a method of generating polyclonal or monoclonal human antibodies against protein tyrosine kinase polypeptides and peptides of the invention, or fragments thereof, comprising EBV-transformation of human B cells.

Antibody fragments that recognize specific epitopes can be generated by known techniques. For example, Fab and F(ab′)2 fragments of the invention can be produced by proteolytic cleavage of immunoglobulin molecules, using enzymes such as papain (to produce Fab fragments) or pepsin (to produce F (ab′)2 fragments). F(ab′)2 fragments contain the variable region, the light chain constant region and the CH1 domain of the heavy chain.

Antibodies encompassed by the present invention can also be generated using various phage display methods known in the art. In phage display methods, functional antibody domains are displayed on the surface of phage particles which carry the polynucleotide sequences encoding them. In a particular embodiment, such phage can be utilized to display antigen binding domains expressed from a repertoire or combinatorial antibody library (e.g., human or murine). Phage expressing an antigen binding domain that binds to the antigen of interest can be selected or identified with antigen, e.g., using labeled antigen or antigen bound or captured onto a solid surface or bead. Phage used in these methods are typically filamentous phage including fd and M13 binding domains expressed from phage with Fab, Fv, or disulfide stabilized antibody domains recombinantly fused to either the phage polynucleotide III or polynucleotide VIII protein. Examples of phage display methods that can be used to make the antibodies of the present invention include those disclosed in Brinkman et al., 1995, J. Immunol. Methods, 182:41-50; Ames et al., 1995, J. Immunol. Methods, 184:177-186; Kettleborough et al., 1994, Eur. J. Immunol., 24:952-958; Persic et al., 1997, Gene, 187:9-18; Burton et al., 1994, Advances in Immunology, 57:191-280; PCT application No. PCT/GB91/01134; PCT publications WO 90/02809; WO 91/10737; WO 92/01047; WO 92/18619; WO 93/11236; WO 95/15982; WO 95/20401; and U.S. Pat. Nos. 5,698,426; 5,223,409; 5,403,484; 5,580,717; 5,427,908; 5,750,753; 5,821,047; 5,571,698; 5,427,908; 5,516,637; 5,780,225; 5,658,727; 5,733,743 and 5,969,108, each of which is incorporated herein by reference in its entirety.

As described in the above references, after phage selection, the antibody coding regions from the phage can be isolated and used to generate whole antibodies, including human antibodies, or any other desired antigen binding fragment, and expressed in any desired host, including mammalian cells, insect cells, plant cells, yeast, and bacteria, e.g., as described in detail below.

Examples of techniques that can be used to produce single-chain Fvs and antibodies include those described in U.S. Pat. Nos. 4,946,778 and 5,258,498; Huston et al., 1991, Methods in Enzymology, 203:46-88; Shu et al., 1993, Proc. Natl. Acad. Sci. USA, 90:7995-7999; and Skerra et al., 1988, Science, 240:1038-1040. For some uses, including the in vivo use of antibodies in humans and in in vitro detection assays, it may be preferable to use chimeric, humanized, or human antibodies. A chimeric antibody is a molecule in which different portions of the antibody are derived from different animal species, such as antibodies having a variable region derived from a murine monoclonal immunoglobulin and a human immunoglobulin constant region. Methods for producing chimeric antibodies are known in the art. (See, e.g., Morrison, 1985, Science, 229:1202; Oi et al., 1986, BioTechniques, 4:214; Gillies et al., 1989, J. Immunol. Methods, 125:191-202; and U.S. Pat. Nos. 5,807,715; 4,816,567; and 4,816,397, which are incorporated herein by reference in their entirety).

Humanized antibodies are antibody molecules from non-human species that bind to the desired antigen and have one or more complementarity determining regions (CDRs) from the nonhuman species and framework regions from a human immunoglobulin molecule. Often, framework residues in the human framework regions are substituted with corresponding residues from the CDR and framework regions of the donor antibody to alter, preferably improve, antigen binding. These framework substitutions are identified by methods well known in the art, e.g., by modeling of the interactions of the CDR and framework residues to identify framework residues important for antigen binding, and by sequence comparison to identify unusual framework residues at particular positions. (See, e.g., Queen et al., U.S. Pat. Nos. 5,693,762 and 5,585,089; and Riechmann et al., 1988, Nature, 332:323, which are incorporated herein by reference in their entireties). Antibodies can be humanized using a variety of techniques known in the art, including, for example, CDR-grafting (EP 239,400; PCT publication WO 91/09967; U.S. Pat. Nos. 5,225,539; 5,530,101; and 5,585,089); veneering or resurfacing (EP 592,106; EP 519,596; Padlan, 1991, Molecular Immunology, 28(4/5):489-498; Studnicka et al., 1994, Protein Engineering, 7(6):805-814; Roguska et al., 1994, Proc. Natl. Acad. Sci. USA, 91:969-973; and chain shuffling (U.S. Pat. No. 5,565,332).

Completely human antibodies can be made by a variety of methods known in the art, including the phage display methods described above, using antibody libraries derived from human immunoglobulin sequences. See also, U.S. Pat. Nos. 4,444,887 and 4,716,111; and PCT publications WO 98/46645, WO 98/50433, WO 98/24893, WO 98/16654, WO 96/34096, WO 96/33735, and WO 91/10741; each of which is incorporated herein by reference in its entirety.

Completely human antibodies are particularly desirable for therapeutic treatment of human patients, so as to avoid or alleviate immune reaction to foreign protein. Human antibodies can be made by a variety of methods known in the art, including the phage display methods described above, using antibody libraries derived from human immunoglobulin sequences. See also, U.S. Pat. Nos. 4,444,887 and 4,716,111; and PCT publications WO 98/46645, WO 98/50433, WO 98/24893, WO 98/16654, WO 96/34096, WO 96/33735, and WO 91/10741; each of which is incorporated herein by reference in its entirety.

Human antibodies can also be produced using transgenic mice which are incapable of expressing functional endogenous immunoglobulins, but which can express human immunoglobulin polynucleotides. For example, the human heavy and light chain immunoglobulin polynucleotide complexes can be introduced randomly, or by homologous recombination, into mouse embryonic stem cells. Alternatively, the human variable region, constant region, and diversity region may be introduced into mouse embryonic stem cells, in addition to the human heavy and light chain polynucleotides. The mouse heavy and light chain immunoglobulin polynucleotides can be rendered nonfunctional separately or simultaneously with the introduction of human immunoglobulin loci by homologous recombination. In particular, homozygous deletion of the J_(H) region prevents endogenous antibody production. The modified embryonic stem cells are expanded and microinjected into blastocysts to produce chimeric mice. The chimeric mice are then bred to produce homozygous offspring which express human antibodies. The transgenic mice are immunized in the normal fashion with a selected antigen, e.g., all or a portion of a polypeptide of the invention.

Thus, using such a technique, it is possible to produce useful human IgG, IgA, IgM, IgD and IgE antibodies. For an overview of the technology for producing human antibodies, see Lonberg and Huszar, 1995, Intl. Rev. Immunol., 13:65-93. For a detailed discussion of the technology for producing human antibodies and human monoclonal antibodies and protocols for producing such antibodies, see, e.g., PCT publications WO 98/24893; WO 92/01047; WO 96/34096; WO 96/33735; European Patent No. 0 598 877; U.S. Pat. Nos. 5,413,923; 5,625,126; 5,633,425; 5,569,825; 5,661,016; 5,545,806; 5,814,318; 5,885,793; 5,916,771; 5,939,598; 6,075,181; and 6,114,598, which are incorporated by reference herein in their entirety. In addition, companies such as Abgenix, Inc. (Fremont, Calif.), Protein Design Labs, Inc. (Mountain View, Calif.) and Genpharm (San Jose, Calif.) can be engaged to provide human antibodies directed against a selected antigen using technology similar to the above described technologies.

Completely human antibodies which recognize a selected epitope can be generated using a technique referred to as “guided selection”. In this approach, a selected non-human monoclonal antibody, e.g., a mouse antibody, is used to guide the selection of a completely human antibody recognizing the same epitope. (Jespers et al., 1988, BioTechnology, 12:899-903).

Further, antibodies to the protein tyrosine kinase polypeptides of the invention can, in turn, be utilized to generate anti-idiotypic antibodies that “mimic” protein tyrosine kinase biomarker polypeptides of the invention using techniques well known to those skilled in the art. (See, e.g., Greenspan and Bona, 1989, FASEB J., 7(5):437-444 and Nissinoff, 1991, J. Immunol., 147(8):2429-2438). For example, antibodies which bind to and competitively inhibit polypeptide multimerization and/or binding of a polypeptide of the invention to a ligand can be used to generate anti-idiotypes that “mimic” the polypeptide multimerization and/or binding domain and, as a consequence, bind to and neutralize the polypeptide and/or its ligand, e.g., in therapeutic regimens. Such neutralizing anti-idiotypes or Fab fragments of such anti-idiotypes can be used to neutralize polypeptide ligand. For example, such anti-idiotypic antibodies can be used to bind a polypeptide of the invention and/or to bind its ligands/receptors, and thereby activate or block its biological activity.

Intrabodies are antibodies, often scFvs, that are expressed from a recombinant nucleic acid molecule and are engineered to be retained intracellularly (e.g., retained in the cytoplasm, endoplasmic reticulum, or periplasm of the host cells). Intrabodies can be used, for example, to ablate the function of a protein to which the intrabody binds. The expression of intrabodies can also be regulated through the use of inducible promoters in the nucleic acid expression vector comprising nucleic acid encoding the intrabody. Intrabodies of the invention can be produced using methods known in the art, such as those disclosed and reviewed in Chen et al., 1994, Hum. Polynucleotide Ther., 5:595-601; Marasco, W. A., 1997, Polynucleotide Ther., 4:11-15; Rondon and Marasco, 1997, Annu. Rev. Microbiol., 51:257-283; Proba et al., 1998, J. Mol. Biol., 275:245-253; Cohen et al., 1998, Oncogene, 17:2445-2456; Ohage and Steipe, 1999, J. Mol. Biol., 291:1119-1128; Ohage et al., 1999, J. Mol. Biol., 291:1129-1134; Wirtz and Steipe, 1999, Protein Sci., 8:2245-2250; and Zhu et al., 1999, J. Immunol. Methods, 231:207-222.

XenoMouse Technology Antibodies in accordance with the invention are preferably prepared by the utilization of a transgenic mouse that has a substantial portion of the human antibody producing genome inserted into its genome, but that is rendered deficient in the production of endogenous murine antibodies (e.g., XenoMouse strains available from Abgenix Inc., Fremont, Calif.). Such mice are capable of producing human immunoglobulin molecules and are virtually deficient in the production of murine immunoglobulin molecules. Technologies utilized for achieving the same are disclosed in the patents, applications, and references disclosed herein.

The ability to clone and reconstruct megabase-sized human loci in YACs and to introduce them into the mouse germline provides a powerful approach to elucidating the functional components of very large or crudely mapped loci, as well as generating useful models of human disease. Furthermore, the utilization of such technology for substitution of mouse loci with their human equivalents could provide unique insights into the expression and regulation of human polynucleotide products during development, their communication with other systems, and their involvement in disease induction and progression. An important practical application of such a strategy is the “humanization” of the mouse humoral immune system. Introduction of human immunoglobulin (Ig) loci into mice in which the endogenous Ig polynucleotides have been inactivated offers the opportunity to study the mechanisms underlying programmed expression and assembly of antibodies as well as their role in B cell development. Furthermore, such a strategy could provide an ideal source for the production of fully human monoclonal antibodies (Mabs), which is an important milestone toward fulfilling the promise of antibody therapy in human disease.

Fully human antibodies are expected to minimize the immunogenic and allergic responses intrinsic to mouse or mouse-derivatized monoclonal antibodies and thus to increase the efficacy and safety of the administered antibodies. The use of fully human antibodies can be expected to provide a substantial advantage in the treatment of chronic and recurring human diseases, such as cancer, which require repeated antibody administrations.

One approach toward this goal was to engineer mouse strains deficient in mouse antibody production to harbor large fragments of the human Ig loci in anticipation that such mice would produce a large repertoire of human antibodies in the absence of mouse antibodies. Large human Ig fragments would preserve the large variable polynucleotide diversity as well as the proper regulation of antibody production and expression. By exploiting the mouse machinery for antibody diversification and selection and the lack of immunological tolerance to human proteins, the reproduced human antibody repertoire in these mouse strains should yield high affinity antibodies against any antigen of interest, including human antigens. Using the hybridoma technology, antigen-specific human monoclonal antibodies with the desired specificity could be readily produced and selected.

This general strategy was demonstrated in connection with the generation of the first “XenoMouseT” strains as published in 1994. See Green et al., 1994, Nature Genetics, 7:13-21. The XenoMouse strains were engineered with yeast artificial chromosomes (YACS) containing 245 kb and 10, 190 kb-sized germline configuration fragments of the human heavy chain locus and kappa light chain locus, respectively, which contained core variable and constant region sequences. Id. The human Ig-containing YACs proved to be compatible with the mouse system for both rearrangement and expression of antibodies and were capable of substituting for the inactivated mouse Ig polynucleotides. This was demonstrated by their ability to induce B-cell development, to produce an adult-like human repertoire of fully human antibodies, and to generate antigen-specific human monoclonal antibodies. These results also suggested that introduction of larger portions of the human Ig loci containing greater numbers of V polynucleotides, additional regulatory elements, and human Ig constant regions might recapitulate substantially the full repertoire that is characteristic of the human humoral response to infection and immunization. The work of Green et al. was recently extended to the introduction of greater than approximately 80% of the human antibody repertoire through the use of megabase-sized, germline configuration YAC fragments of the human heavy chain loci and kappa light chain loci, respectively, to produce XenoMouse mice. See Mendez et al., 1997, Nature Genetics, 15:146-156; Green and Jakobovits, 1998, J. Exp. Med., 188:483-495; and Green, 1999, Journal of Immunological Methods, 231:11-23, the disclosures of which are hereby incorporated herein by reference.

Human anti-mouse antibody (HAMA) responses have led the industry to prepare chimeric or otherwise humanized antibodies. While chimeric antibodies typically are comprised of a human constant region and a murine variable region, it is expected that certain human anti-chimeric antibody (HACA) responses will be observed, particularly in treatments involving chronic or multi-dose utilizations of the antibody. Thus, it is desirable to provide fully human antibodies against protein tyrosine kinase biomarker polypeptides in order to vitiate concerns and/or effects of HAMA or HACA responses.

Antibodies of the invention can be chemically synthesized or produced through the use of recombinant expression systems. Accordingly, the invention further embraces polynucleotides comprising a nucleotide sequence encoding an antibody of the invention and fragments thereof. The invention also encompasses polynucleotides that hybridize under stringent or lower stringency hybridization conditions, e.g., as defined supra, to polynucleotides that encode an antibody, preferably, an antibody that specifically binds to a protein tyrosine kinase polypeptide of this invention, and more preferably, an antibody that binds to a polypeptide having the amino acid sequence of one or more of the protein tyrosine kinase biomarker sequences, e.g., Src tyrosine kinase biomarkers, as set forth in Table 2.

The polynucleotides may be obtained, and the nucleotide sequence of the polynucleotides determined, by any method known in the art. For example, if the nucleotide sequence of the antibody is known, a polynucleotide encoding the antibody can be assembled from chemically synthesized oligonucleotides (e.g., as described in Kutmeier et al., 1994, BioTechniques, 17:242), which, briefly, involves the synthesis of overlapping oligonucleotides containing portions of the sequence encoding the antibody, the annealing and ligating of those oligonucleotides, and then the amplification of the ligated oligonucleotides by PCR.

Alternatively, a polynucleotide encoding an antibody can be generated from nucleic acid from a suitable source. If a clone containing a nucleic acid encoding a particular antibody is not available, but the sequence of the antibody molecule is known, a nucleic acid encoding the immunoglobulin can be chemically synthesized or obtained from a suitable source (e.g., an antibody cDNA library, or a cDNA library generated from, (or a nucleic acid, preferably poly A+ RNA, isolated from), any tissue or cells expressing the antibody, such as hybridoma cells selected to express an antibody of the invention by PCR amplification using synthetic primers hybridizable to the 3′ and 5′ ends of the sequence. Alternatively, cloning using an oligonucleotide probe specific for the particular polynucleotide sequence to be identified, e.g., a cDNA clone from a cDNA library that encodes the desired antibody can be employed. Amplified nucleic acids generated by PCR can then be cloned into replicable cloning vectors using any method well known in the art.

Once the nucleotide sequence and corresponding encoded amino acid sequence of the antibody are determined, the nucleotide sequence of the antibody can be manipulated using methods well known in the art for the manipulation of nucleotide sequences, e.g., recombinant DNA techniques, site directed mutapolynucleotidesis, PCR, etc. (see, for example, the techniques described in Sambrook et al., 1990, Molecular Cloning, A Laboratory Manual, 2nd Ed., Cold Spring Harbor Laboratory, Cold Spring Harbor, N.Y.; and F. M. Ausubel et al., eds., 1998, Current Protocols in Molecular Biology, John Wiley & Sons, NY, which are both incorporated by reference herein in their entireties), to generate antibodies having a different amino acid sequence, for example, to create amino acid substitutions, deletions, and/or insertions.

In a specific embodiment, the amino acid sequence of the heavy and/or light chain variable domains can be inspected to identify the sequences of the CDRs by methods that are well known in the art, e.g., by comparison to known amino acid sequences of other heavy and light chain variable regions, to determine the regions of sequence hypervariability. Using routine recombinant DNA techniques, one or more of the CDRs can be inserted within framework regions, e.g., into human framework regions, to humanize a non-human antibody, as described supra. The framework regions can be naturally occurring or consensus framework regions, and preferably, are human framework regions (see, e.g., Chothia et al., 1998, J. Mol. Biol., 278:457-479, for a listing of human framework regions).

Preferably, the polynucleotide generated by the combination of the framework regions and CDRs encodes an antibody that specifically binds to a protein tyrosine kinase biomarker polypeptide of the invention. Also preferably, as discussed supra, one or more amino acid substitutions can be made within the framework regions; such amino acid substitutions are performed with the goal of improving binding of the antibody to its antigen, e.g., greater antibody binding affinity. In addition, such methods can be used to make amino acid substitutions or deletions of one or more variable region cysteine residues participating in an intrachain disulfide bond to generate antibody molecules lacking one or more intrachain disulfide bonds. Other alterations that can be made to the polynucleotide are encompassed by the present invention and are within the skill of the art.

For some uses, such as for in vitro affinity maturation of an antibody of the invention, it is useful to express the V_(H) and V_(L) domains of the heavy and light chains of one or more antibodies of the invention as single chain antibodies, or Fab fragments, in a phage display library using phage display methods as described supra. For example, the cDNAs encoding the V_(H) and V_(L) domains of one or more antibodies of the invention can be expressed in all possible combinations using a phage display library, thereby allowing for the selection of V_(H)/V_(L) combinations that bind to the protein tyrosine kinase biomarker polypeptides according to the present invention with preferred binding characteristics such as improved affinity or improved off rates. In addition, V_(H) and V_(L) segments, particularly, the CDR regions of the V_(H) and V_(L) domains of one or more antibodies of the invention, can be mutated in vitro. Expression of V_(H) and V_(L) domains with “mutant” CDRs in a phage display library allows for the selection of V_(H)/V_(L) combinations that bind to protein tyrosine kinase biomarkers, e.g., Src tyrosine kinase biomarker proteins, which are receptor polypeptides with preferred binding characteristics such as improved affinity or improved off rates.

Once an antibody molecule of the invention has been produced by an animal, chemically synthesized, or recombinantly expressed, it can be purified by any method known in the art for the purification of an immunoglobulin or polypeptide molecule, for example, by chromatography (e.g., ion exchange, affinity, particularly by affinity for the specific antigen, Protein A, and sizing column chromatography), centrifugation, differential solubility, or by any other standard technique for the purification of proteins. In addition, the antibodies of the present invention or fragments thereof can be fused to heterologous polypeptide sequences described herein or otherwise known in the art, to facilitate purification.

The present invention encompasses antibodies that are recombinantly fused or chemically conjugated (including both covalently and non-covalently conjugated) to a polypeptide (or portion thereof, preferably at least 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100 amino acids of the polypeptide) of the present invention to generate fusion proteins. The fusion does not necessarily need to be direct, but can occur through linker sequences. The antibodies can be specific for antigens other than polypeptides (or portions thereof, preferably at least 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100 amino acids of the polypeptide) of the present invention. For example, antibodies can be used to target the polypeptides of the present invention to particular cell types, either in vitro or in vivo, by fusing or conjugating the polypeptides of the present invention to antibodies specific for particular cell surface receptors.

The present invention further includes compositions comprising the protein tyrosine kinase biomarker polypeptides of the present invention fused or conjugated to antibody domains other than the variable region domain. For example, the polypeptides of the present invention can be fused or conjugated to an antibody Fc region, or portion thereof. The antibody portion fused to a polypeptide of the present invention can comprise the constant region, hinge region, CH1 domain, CH2 domain, CH3 domain, or any combination of whole domains or portions thereof. The polypeptides can also be fused or conjugated to the above antibody portions to form multimers. For example, Fc portions of immunoglobulin molecules fused to the polypeptides of the present invention can form dimers through disulfide bonding between the Fc portions. Higher multimeric forms can be made by fusing the polypeptides to portions of IgA and IgM. Methods for fusing or conjugating the polypeptides of the present invention to antibody portions are known in the art. (See, e.g., U.S. Pat. Nos. 5,336,603; 5,622,929; 5,359,046; 5,349,053; 5,447,851; 5,112,946; EP 307,434; EP 367,166; PCT publications WO 96/04388; WO 91/06570; Ashkenazi et al., 1991, Proc. Natl. Acad. Sci. USA, 88:10535-10539; Zheng et al., 1995, J. Immunol., 154:5590-5600; and Vil et al., Proc. Natl. Acad. Sci. USA, 89:11337-11341, which are hereby incorporated by reference herein in their entireties).

As discussed supra, the polypeptides corresponding to a polypeptide, polypeptide fragment, or a variant of one or more of the protein tyrosine kinase biomarker amino acid sequences as set forth in Table 2 can be fused or conjugated to the above antibody portions to increase the in vivo half life of the polypeptides, or for use in immunoassays using methods known in the art. Further, the polypeptides corresponding to one or more of the protein tyrosine kinase biomarker, e.g., src biomarker, sequences as set forth in Table 2 can be fused or conjugated to the above antibody portions to facilitate purification. For guidance, chimeric proteins having the first two domains of the human CD4 polypeptide and various domains of the constant regions of the heavy or light chains of mammalian immunoglobulins have been described. (EP 394,827; Traunecker et al., 1988, Nature, 331:84-86). The polypeptides of the present invention fused or conjugated to an antibody, or portion thereof, having disulfide-linked dimeric structures (due to the IgG), for example, can also be more efficient in binding and neutralizing other molecules than the monomeric secreted protein or protein fragment alone. (Fountoulakis et al., 1995, J. Biochem., 270:3958-3964). In many cases, the Fc portion in a fusion protein is beneficial in therapy, diagnosis, and/or screening methods, and thus can result in, for example, improved pharmacokinetic properties. (EP 232, 262 A). In drug discovery, for example, human proteins, such as huIL-5, have been fused with Fc portions for the purpose of high-throughput screening assays to identify antagonists of huIL-5. (See, Bennett et al., 1995, J. Molecular Recognition, 8:52-58; and Johanson et al., 1995, J. Biol. Chem., 270:9459-9471). Alternatively, deleting the Fc portion after the fusion protein has been expressed, detected, and purified may be desired. For example, the Fc portion may hinder therapy and diagnosis if the fusion protein is used as an antigen for immunizations.

Moreover, the antibodies or fragments thereof of the present invention can be fused to marker sequences, such as a peptide, to facilitate their purification. In preferred embodiments, the marker amino acid sequence is a hexa-histidine peptide, such as the tag provided in a pQE vector (QIAGEN, Inc., Chatsworth, Calif.), among others, many of which are commercially available. As described in Gentz et al., 1989, Proc. Natl. Acad. Sci. USA, 86:821-824, for instance, hexa-histidine provides for convenient purification of the fusion protein. Other peptide tags useful for purification include, but are not limited to, the “HA” tag, which corresponds to an epitope derived from the influenza hemagglutinin (HA) protein (Wilson et al., 1984, Cell, 37:767) and the “flag” tag.

The present invention further encompasses antibodies or fragments thereof conjugated to a diagnostic or therapeutic agent. The antibodies can be used diagnostically to, for example, monitor the development or progression of a tumor as part of a clinical testing procedure, for example, to determine the efficacy of a given treatment regimen. Detection can be facilitated by coupling the antibody to a detectable substance. Nonlimiting examples of detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, radioactive materials, positron emitting metals using various positron emission tomographies, and nonradioactive paramagnetic metal ions. The detectable substance can be coupled or conjugated either directly to the antibody (or fragment thereof) or indirectly, through an intermediate (such as, for example, a linker known in the art) using techniques known in the art. (See, for example, U.S. Pat. No. 4,741,900 for metal ions which can be conjugated to antibodies for use as diagnostics according to the present invention).

Nonlimiting examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, beta-galactosidase, or acetylcholinesterase. Nonlimiting examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; nonlimiting examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride or phycoerythrin; a nonlimiting example of a luminescent material includes luminol; nonlimiting examples of bioluminescent materials include luciferase, luciferin, and aequorin; and nonlimiting examples of suitable radioactive material include iodine (¹²⁵I, ¹³¹I), carbon (¹⁴C), sulfur (3sus), tritium (³H), indium (¹¹¹In and other radioactive isotopes of inidium), technetium (⁹⁹Tc, ^(99m)Tc), thallium (20′Ti), gallium (⁶⁸Ga, ⁶⁷Ga), palladium (¹⁰³Pd), molybdenum (⁹⁹Mo), xenon (¹³³Xe), fluorine (¹⁹F), ¹⁵³Sm, ¹⁷⁷Lu, Gd, radioactive Pm, radioactive La, radioactive Yb, ¹⁶⁶Ho, ⁹⁰Y, radioactive Sc, radioactive Re, radioactive Re, ¹⁴²Pr, ¹⁰⁵Rh, and ⁹⁷Ru.

In specific embodiments, the protein tyrosine kinase biomarker polypeptides of the invention are attached to macrocyclic chelators useful for conjugating radiometal ions, including, but not limited to, ¹¹¹In, ¹⁷⁷Lu, ⁹⁰Y, ¹⁶⁶Ho, and ¹⁵³Sm, to polypeptides. In a preferred embodiment, the radiometal ion associated with the macrocyclic chelators attached to the protein tyrosine kinase biomarker polypeptides of the invention is ¹¹¹In. In another preferred embodiment, the radiometal ion associated with the macrocyclic chelator attached to the protein tyrosine kinase biomarker polypeptides of the invention is ⁹⁰Y. In specific embodiments, the macrocyclic chelator is 1,4,7,10-tetraazacyclododecane-N,N′,N″,N′″-tetraacetic acid (DOTA). In other specific embodiments, the DOTA is attached to the protein tyrosine kinase biomarker polypeptides of the invention via a linker molecule.

Examples of linker molecules useful for conjugating DOTA to a polypeptide are commonly known in the art. (See, for example, DeNardo et al., 1998, Clin. Cancer Res., 4(10):2483-90; Peterson et al., 1999, Bioconjug. Chem., 10(4):553-557; and Zimmerman et al, 1999, Nucl. Med. Biol., 26(8):943-950, which are hereby incorporated by reference in their entirety). In addition, U.S. Pat. Nos. 5,652,361 and 5,756,065, which disclose chelating agents that can be conjugated to antibodies and methods for making and using them, are hereby incorporated by reference in their entireties. Though U.S. Pat. Nos. 5,652,361 and 5,756,065 focus on conjugating chelating agents to antibodies, one skilled in the art can readily adapt the methods disclosed therein in order to conjugate chelating agents to other polypeptides.

Antibodies can also be attached to solid supports, which are particularly useful for immunoassays or purification of the target antigen. Such solid supports include, but are not limited to, glass, cellulose, polyacrylamide, nylon, polystyrene, polyvinyl chloride or polypropylene. Techniques for conjugating therapeutic moieties to antibodies are well known, see, e.g., Arnon et al., “Monoclonal Antibodies For Immunotargeting Of Drugs In Cancer Therapy”, In: Monoclonal Antibodies And Cancer Therapy, Reisfeld et al. (eds.), pp. 243-56, Alan R. Liss, Inc., 1985; Hellstrom et al., “Antibodies For Drug Delivery”, In: Controlled Drug Delivery (2nd Ed.), Robinson et al. (eds.), pp. 623-53, Marcel Deldcer, Inc., 1987; Thorpe, “Antibody Carriers Of Cytotoxic Agents In Cancer Therapy: A Review”, In: Monoclonal Antibodies '84: Biological And Clinical Applications, Pinchera et al. (eds.), pp. 475-506, 1985; “Analysis, Results, And Future Prospective Of The Therapeutic Use Of Radiolabeled Antibody In Cancer Therapy”, In: Monoclonal Antibodies For Cancer Detection And Therapy, Baldwin et al. (eds.), pp. 303-316, Academic Press, 1985; and Thorpe et al., 1982, “The Preparation And Cytotoxic Properties Of Antibody-Toxin Conjugates”, Immunol. Rev., 62:119-158. Alternatively, an antibody can be conjugated to a second antibody to form an antibody heteroconjugate, e.g., as described in U.S. Pat. No. 4,676,980 to Segal, which is incorporated herein by reference in its entirety. An antibody, i.e., an antibody specific for a protein tyrosine kinase biomarker polypeptide of this invention, with or without a therapeutic moiety conjugated to it, and administered alone or in combination with cytotoxic factor(s) and/or cytokine(s), can be used as a therapeutic.

The antibodies of the invention can further be utilized for immunophenotyping of cell lines and biological samples. The translation product of the protein tyrosine kinase biomarker-encoding polynucleotides of the present invention can be useful as cell specific marker(s), or more specifically, as cellular marker(s) that are differentially expressed at various stages of differentiation and/or maturation of particular cell types. Monoclonal antibodies directed against a specific epitope, or combination of epitopes, allow for the screening of cellular populations expressing the marker. Various techniques utilizing monoclonal antibodies can be employed to screen for cellular populations expressing the marker(s), including magnetic separation using antibody-coated magnetic beads, “panning” with antibody(ies) attached to a solid matrix (i.e., tissue culture plate), and flow cytometry (See, e.g., U.S. Pat. No. 5,985,660; Morrison et al., 1999, Cell, 96:737-749; and L. J. Wysocki and V. L. Sato, 1978, Proc. Natl. Acad. Sci. USA, 75(6):2844-8).

These techniques allow for the screening of particular populations of cells, such as might be found with hematological malignancies (i.e. minimal residual disease (MRD) in acute leukemic patients) and “non-self” cells in transplantations to prevent Graft-versus-Host Disease (GVHD). Alternatively, these techniques allow for the screening of hematopoietic stem and progenitor cells capable of undergoing proliferation and/or differentiation, as might be found in human umbilical cord blood.

Antibodies according to this invention can be assayed for immunospecific binding by any method known in the art. The immunoassays which can be used include, but are not limited to, competitive and non-competitive assay systems using techniques such as BIAcore analysis, FACS (Fluorescence Activated Cell Sorter) analysis, immunofluorescence, immunocytochemistry, Western blots, radioimmunoassays, ELISA (enzyme linked immunosorbent assays), “sandwich” immunoassays, immunoprecipitation assays, precipitin reactions, gel diffusion precipitin reactions, immunodiffusion assays, agglutination assays, complement fixation assays, immunoradiometric assays, fluorescent immunoassays, protein A immunoassays, to name but a few. Such assays are routine and well known and practiced in the art (see, e.g., Ausubel et al, eds, 1994, Current Protocols in Molecular Biology, Vol. 1, John Wiley & Sons, Inc., New York, which is incorporated by reference herein in its entirety). Nonlimiting, exemplary immunoassays are described briefly below.

Immunoprecipitation protocols generally comprise lysing a population of cells in a lysis buffer such as RIPA buffer (i.e., 1% NP-40 or Triton X-100, 1% sodium deoxycholate, 0.1% SDS, 0.15 M NaCl, 0.01 M sodium phosphate at pH 7.2, 1% Trasylol) supplemented with protein phosphatase and/or protease inhibitors (e.g., EDTA, PMSF, aprotinin, sodium vanadate); adding the antibody of interest to the cell lysate; incubating for a period of time (e.g., 1 to 4 hours) at 4° C.; adding protein A and/or protein G sepharose beads to the cell lysate; incubating for about 60 minutes or more at 4° C.; washing the beads in lysis buffer; and resuspending the beads in SDS/sample buffer. The ability of the antibody of interest to immunoprecipitate a particular antigen can be assessed by, for example, Western blot analysis. One of skill in the art would be knowledgeable as to the parameters that can be modified to increase the binding of the antibody to an antigen and decrease the background (e.g., pre-clearing the cell lysate with sepharose beads). For further discussion regarding immunoprecipitation protocols, see, e.g., Ausubel et al, eds, 1994, Current Protocols in Molecular Biology, Vol. 1, John Wiley & Sons, Inc., New York, at 10.16.1.

Western blot analysis generally comprises preparing protein samples; electrophoresis of the protein samples in a polyacrylamide gel (e.g., 8%-20% SDS PAGE depending on the molecular weight of the antigen); transferring the protein sample from the polyacrylamide gel to a membrane such as nitrocellulose, PVDF or nylon; blocking the membrane in blocking solution (e.g., PBS with 3% BSA or nonfat milk); washing the membrane in washing buffer (e.g., PBS-Tween 20); blocking the membrane with primary antibody (the antibody of interest) diluted in blocking buffer; washing the membrane in washing buffer; blocking the membrane with a secondary antibody (which recognizes the primary antibody, e.g., an anti-human antibody) conjugated to an enzymatic substrate (e.g., horseradish peroxidase or alkaline phosphatase) or radioactive molecule (e.g., ³²P or ¹²⁵I) diluted in blocking buffer; washing the membrane in wash buffer; and detecting the presence of the bound antigen. One of skill in the art would be knowledgeable as to the parameters that can be modified to increase the signal detected and to reduce the background noise. For further discussion regarding Western blot protocols, see, e.g., Ausubel et al, eds, 1994, Current Protocols in Molecular Biology, Vol. 1, John Wiley & Sons, Inc., New York, at 10.8.1.

ELISAs comprise preparing antigen; coating the wells of a 96 well microtiter plate with antigen; adding to the wells the antibody of interest conjugated to a detectable compound such as an enzymatic substrate (e.g., horseradish peroxidase or alkaline phosphatase); incubating for a period of time; and detecting the presence of the antigen. In ELISAs, the antibody of interest does not have to be conjugated to a detectable compound; instead, a second antibody (which recognizes the antibody of interest bound to antigen) conjugated to a detectable compound can be added to the wells. Further, instead of coating the wells with antigen, the antibodies can be first coated onto the well. In this case, a second antibody conjugated to a detectable compound can be added to the antibody-coated wells following the addition of the antigen of interest. One of skill in the art would be knowledgeable as to the parameters that can be modified to increase the signal detected, as well as other variations of ELISAs known in the art. For further discussion regarding ELISAs, see, e.g., Ausubel et al, eds, 1994, Current Protocols in Molecular Biology, Vol. 1, John Wiley & Sons, Inc., New York, at 11.2.1.

The binding affinity of an antibody to an antigen and the off-rate of an antibody-antigen interaction can be determined by competitive binding assays. One example of a competitive binding assay is a radioimmunoassay involving the incubation of labeled antigen (e.g., ³H or ¹²⁵I), or a fragment or variant thereof, with the antibody of interest in the presence of increasing amounts of labeled antigen, and the detection of the antibody bound to the labeled antigen. The affinity of the antibody of interest for a protein tyrosine kinase biomarker and the binding off rates can be determined from the data by Scatchard plot analysis. Competition with a second antibody can also be determined using radioimmunoassays. In this case, the tyrosine kinase biomarker protein is incubated with an antibody of interest conjugated to a labeled compound (e.g., a compound labeled with ³H or ¹²⁵I) in the presence of increasing amounts of an unlabeled second antibody. This kind of competitive assay between two antibodies can also be used to determine if two antibodies bind to the same or different epitopes on an antigen.

In a preferred embodiment, BIAcore kinetic analysis is used to determine the binding on and off rates of antibodies (including antibody fragments or variants thereof) to a tyrosine kinase biomarker protein, or fragments of a tyrosine kinase biomarker protein. Kinetic analysis comprises analyzing the binding and dissociation of antibodies from chips with immobilized tyrosine kinase biomarker protein on the chip surface.

It is to be further understood that the above-described techniques for the production, expression, isolation, and manipulation of antibody molecules, for example, by recombinant techniques involving molecular biology, as well as by other techniques related to the analysis of polynucleotides and proteins, are applicable to other polypeptide or peptide molecules of the invention as described herein, in particular, the tyrosine kinase biomarker polypeptides or peptides themselves, as applicable or warranted. in accordance with the various embodiments of this invention.

The present invention also embraces a kit for determining, predicting, or prognosing drug susceptibility or resistance by a patient having a disease, particularly a cancer or tumor, preferably, a breast cancer or tumor. Such kits are useful in a clinical setting for use in testing patient's biopsied tumor or cancer samples, for example, to determine or predict if the patient's tumor or cancer will be resistant or sensitive to a given treatment or therapy with a drug, compound, chemotherapy agent, or biological treatment agent. Provided in the kit are the predictor set comprising those polynucleotides correlating with resistance and sensitivity to protein tyrosine kinase modulators in a particular biological system, particularly protein tyrosine kinase inhibitors, and preferably comprising a microarray; and, in suitable containers, the modulator compounds for use in testing cells from patient tissue or patient samples for resistance/sensitivity; and instructions for use. Such kits encompass predictor set comprising those polynucleotides correlating with resistance and sensitivity to modulators of protein tyrosine kinases including members of the Src family of tyrosine kinases, for example, Src, Fgr, Fyn, Yes, Blk, Hck, Lck and Lyn, as well as other protein tyrosine kinases, including, Bcr-abl, Jak, PDGFR, c-kit and Eph receptors,

Also, as explained above, the kit is not limited to microarrays, but can encompass a variety of methods and systems by which the expression of the predictor/marker polynucleotides can be assayed and/or monitored, both at the level of mRNA and of protein, for example, via PCR assays, e.g., RT-PCR and immunoassay, such as ELISA. In kits for performing PCR, or in situ hybridization, for example, nucleic acid primers or probes from the sequences of one or more of the predictor polynucleotides, such as those described herein, in addition to buffers and reagents as necessary for performing the method, and instructions for use. In kits for performing immunoassays, e.g. ELISAs, immunoblotting assays, and the like, antibodies, or bindable portions thereof, to the protein tyrosine kinase biomarker polypeptides of the invention, or to antigenic or immunogenic peptides thereof, are supplied, in addition to buffers and reagents as necessary for performing the method, and instructions for use. The kits according to the present invention can also comprise predictor polynucleotides as set forth in Table 2, and/or one or more of the specific predictor polynucleotide subsets as presented in Tables 4-5 herein.

In another embodiment, the present invention embraces the use of one or more polynucleotides among those of the predictor polynucleotides identified herein that can serve as targets for the development of drug therapies for disease treatment. Such targets may be particularly applicable to treatment of breast diseases, such as breast cancers or tumors. Indeed, because these predictor polynucleotides are differently expressed in sensitive and resistant cells, their expression pattern is correlated with relative intrinsic sensitivity of cells to treatment with compounds that interact with and inhibit protein tyrosine kinases. Accordingly, the polynucleotides highly expressed in resistant cells can serve as targets for the development of drug therapies for the tumors which are resistant to protein tyrosine kinase inhibitor compounds, for example, Src tyrosine kinase inhibitors.

In another embodiment, the present invention embraces antisense and/or siRNAi reagents as specific modulators of the predictor polynucleotides of the present invention. In specific embodiments, antagonists according to the present invention are nucleic acids corresponding to the sequences contained in one or more of the sequences provided as SEQ ID NO:1 thru 137, or the complementary strand thereof. In one embodiment, antisense sequence is generated internally by the organism, in another embodiment, the antisense sequence is separately administered (see, for example, O'Connor, Neurochem., 56:560 (1991). Oligodeoxynucleotides as Antisense Inhibitors of Gene Expression, CRC Press, Boca Raton, Fla. (1988). Antisense technology can be used to control gene expression through antisense DNA or RNA, or through triple-helix formation. Antisense techniques are discussed for example, in Okano, Neurochem., 56:560 (1991); Oligodeoxynucleotides as Antisense Inhibitors of Gene Expression, CRC Press, Boca Raton, Fla. (1988). Triple helix formation is discussed in, for instance, Lee et al., Nucleic Acids Research, 6:3073 (1979); Cooney et al., Science, 241:456 (1988); and Dervan et al., Science, 251:1300 (1991). The methods are based on binding of a polynucleotide to a complementary DNA or RNA.

For example, the use of c-myc and c-myb antisense RNA constructs to inhibit the growth of the non-lymphocytic leukemia cell line HL-60 and other cell lines was previously described. (Wickstrom et al. (1988); Anfossi et al. (1989)). These experiments were performed in vitro by incubating cells with the oligoribonucleotide. A similar procedure for in vivo use is described in WO 91/15580. Briefly, a pair of oligonucleotides for a given antisense RNA is produced as follows: A sequence complimentary to the first 15 bases of the open reading frame is flanked by an EcoR1 site on the 5 end and a HindIII site on the 3 end. Next, the pair of oligonucleotides is heated at 90° C. for one minute and then annealed in 2× ligation buffer (20 mM TRIS HCl pH 7.5, 10 mM MgCl2, 10 MM dithiothreitol (DTT) and 0.2 mM ATP) and then ligated to the EcoR1/Hind III site of the retroviral vector PMV7 (WO 91/15580).

For example, the 5′ coding portion of a polynucleotide that encodes the mature polypeptide of the present invention may be used to design an antisense RNA oligonucleotide of from about 10 to 40 base pairs in length. A DNA oligonucleotide is designed to be complementary to a region of the gene involved in transcription thereby preventing transcription and the production of the receptor. The antisense RNA oligonucleotide hybridizes to the mRNA in vivo and blocks translation of the mRNA molecule into receptor polypeptide. Antisense oligonucleotides may be single or double stranded. Double stranded RNA's may be designed based upon the teachings of Paddison et al., Proc. Nat. Acad. Sci., 99:1443-1448 (2002); and International Publication Nos. WO 01/29058, and WO 99/32619; which are hereby incorporated herein by reference.

In one embodiment, the antisense nucleic acid of the invention is produced intracellularly by transcription from an exogenous sequence. For example, a vector or a portion thereof, is transcribed, producing an antisense nucleic acid (RNA) of the invention. Such a vector would contain a sequence encoding the antisense nucleic acid of the invention. Such a vector can remain episomal or become chromosomally integrated, as long as it can be transcribed to produce the desired antisense RNA. Such vectors can be constructed by recombinant DNA technology methods standard in the art. Vectors can be plasmid, viral, or others known in the art, used for replication and expression in vertebrate cells. Expression of the sequence encoding a polypeptide of the invention, or fragments thereof, can be by any promoter known in the art to act in vertebrate, preferably human cells. Such promoters can be inducible or constitutive. Such promoters include, but are not limited to, the SV40 early promoter region (Bernoist and Chambon, Nature, 29:304-310 (1981), the promoter contained in the 3′ long terminal repeat of Rous sarcoma virus (Yamamoto et al., Cell, 22:787-797 (1980), the herpes thymidine promoter (Wagner et al., Proc. Natl. Acad. Sci. U.S.A., 78:1441-1445 (1981), the regulatory sequences of the metallothionein gene (Brinster et al., Nature, 296:39-42 (1982)), etc.

The antisense nucleic acids of the invention comprise a sequence complementary to at least a portion of an RNA transcript of a gene of interest. However, absolute complementarity, although preferred, is not required. A sequence “complementary to at least a portion of an RNA” referred to herein, means a sequence having sufficient complementarity to be able to hybridize with the RNA, forming a stable duplex; in the case of double stranded antisense nucleic acids of the invention, a single strand of the duplex DNA may thus be tested, or triplex formation may be assayed. The ability to hybridize will depend on both the degree of complementarity and the length of the antisense nucleic acid Generally, the larger the hybridizing nucleic acid, the more base mismatches with a RNA sequence of the invention it may contain and still form a stable duplex (or triplex as the case may be). One skilled in the art can ascertain a tolerable degree of mismatch by use of standard procedures to determine the melting point of the hybridized complex.

Oligonucleotides that are complementary to the 5′ end of the message, e.g., the 5′ untranslated sequence up to and including the AUG initiation codon, should work most efficiently at inhibiting translation. However, sequences complementary to the 3′ untranslated sequences of mRNAs have been shown to be effective at inhibiting translation of mRNAs as well. See generally, Wagner, R., Nature, 372:333-335 (1994). Thus, oligonucleotides complementary to either the 5′- or 3′-non-translated, non-coding regions of a polynucleotide sequence of the invention could be used in an antisense approach to inhibit translation of endogenous mRNA. Oligonucleotides complementary to the 5′ untranslated region of the mRNA should include the complement of the AUG start codon. Antisense oligonucleotides complementary to mRNA coding regions are less efficient inhibitors of translation but could be used in accordance with the invention. Whether designed to hybridize to the 5′-, 3′- or coding region of mRNA, antisense nucleic acids should be at least six nucleotides in length, and are preferably oligonucleotides ranging from 6 to about 50 nucleotides in length. In specific aspects the oligonucleotide is at least 10 nucleotides, at least 17 nucleotides, at least 25 nucleotides or at least 50 nucleotides.

The polynucleotides of the invention can be DNA or RNA or chimeric mixtures or derivatives or modified versions thereof, single-stranded or double-stranded. The oligonucleotide can be modified at the base moiety, sugar moiety, or phosphate backbone, for example, to improve stability of the molecule, hybridization, etc. The oligonucleotide may include other appended groups such as peptides (e.g., for targeting host cell receptors in vivo), or agents facilitating transport across the cell membrane (see, e.g., Letsinger et al., Proc. Natl. Acad. Sci. U.S.A. 86:6553-6556 (1989); Lemaitre et al., Proc. Natl. Acad. Sci., 84:648-652 (1987); PCT Publication NO: WO88/09810, published Dec. 15, 1988) or the blood-brain barrier (see, e.g., PCT Publication NO: WO89/10134, published Apr. 25, 1988), hybridization-triggered cleavage agents. (See, e.g., Krol et al., BioTechniques, 6:958-976 (1988)) or intercalating agents. (See, e.g., Zon, Pharm. Res., 5:539-549 (1988)). To this end, the oligonucleotide may be conjugated to another molecule, e.g., a peptide, hybridization triggered cross-linking agent, transport agent, hybridization-triggered cleavage agent, etc.

Double stranded RNA's may be designed based upon the teachings of Paddison et al., Proc. Nat. Acad. Sci., 99:1443-1448 (2002); and International Publication Nos. WO 01/29058, and WO 99/32619; which are hereby incorporated herein by reference.

SiRNA reagents are specifically contemplated by the present invention. Such reagents are useful for inhibiting expression of the polynucleotides of the present invention and may have therapeutic efficacy. Several methods are known in the art for the therapeutic treatment of disorders by the administration of siRNA reagents. One such method is described by Tiscomia et al (PNAS, 100(4):1844-1848 (2003)), which is incorporated by reference herein in its entirety.

The antisense oligonucleotide may comprise at least one modified base moiety which is selected from the group including, but not limited to, 5-fluorouracil, 5-bromouracil, 5-chlorouracil, 5-iodouracil, hypoxanthine, xanthine, 4-acetylcytosine, 5-(carboxyhydroxylmethyl) uracil, 5-carboxymethylaminomethyl-2-thiouridine, 5-carboxymethylaminomethyluracil, dihydrouracil, beta-D-galactosylqueosine, inosine, N6-isopentenyladenine, 1-methylguanine, 1-methylinosine, 2,2-dimethylguanine, 2-methyladenine, 2-methylguanine, 3-methylcytosine, 5-methylcytosine, N6-adenine, 7-methylguanine, 5-methylaminomethyluracil, 5-methoxyaminomethyl-2-thiouracil, beta-D-mannosylqueosine, 5′-methoxycarboxymethyluracil, 5-methoxyuracil, 2-methylthio-N-6-isopentenyladenine, uracil-5-oxyacetic acid (v), wybutoxosine, pseudouracil, queosine, 2-thiocytosine, 5-methyl-2-thiouracil, 2-thiouracil, 4-thiouracil, 5-methyluracil, uracil-5-oxyacetic acid methylester, uracil-5-oxyacetic acid (v), 5-methyl-2-thiouracil, 3-(3-amino-3-N-2-carboxypropyl) uracil, (acp3)w, and 2,6-diaminopurine.

The antisense oligonucleotide may also comprise at least one modified sugar moiety selected from the group including, but not limited to, arabinose, 2-fluoroarabinose, xylulose, and hexose.

In yet another embodiment, the antisense oligonucleotide comprises at least one modified phosphate backbone selected from the group including, but not limited to, a phosphorothioate, a phosphorodithioate, a phosphoramidothioate, a phosphoramidate, a phosphordiamidate, a methylphosphonate, an alkyl phosphotriester, and a formacetal or analog thereof.

In yet another embodiment, the antisense oligonucleotide is an a-anomeric oligonucleotide. An a-anomeric oligonucleotide forms specific double-stranded hybrids with complementary RNA in which, contrary to the usual b-units, the strands run parallel to each other (Gautier et al., Nucl. Acids Res., 15:6625-6641 (1987)). The oligonucleotide is a 2-0-methylribonucleotide (Inoue et al., Nucl. Acids Res., 15:6131-6148 (1987)), or a chimeric RNA-DNA analogue (Inoue et al., FEBS Lett. 215:327-330 (1987)).

Polynucleotides of the invention may be synthesized by standard methods known in the art, e.g. by use of an automated DNA synthesizer (such as are commercially available from Biosearch, Applied Biosystems, etc.). As examples, phosphorothioate oligonucleotides may be synthesized by the method of Stein et al. (Nucl. Acids Res., 16:3209 (1988)), methylphosphonate oligonucleotides can be prepared by use of controlled pore glass polymer supports (Sarin et al., Proc. Natl. Acad. Sci. U.S.A., 85:7448-7451 (1988)), etc.

While antisense nucleotides complementary to the coding region sequence of the invention could be used, those complementary to the transcribed untranslated region are most preferred.

Potential antagonists according to the invention also include catalytic RNA, or a ribozyme (See, e.g., PCT International Publication WO 90/11364, published Oct. 4, 1990; Sarver et al, Science, 247:1222-1225 (1990). While ribozymes that cleave mRNA at site specific recognition sequences can be used to destroy mRNAs corresponding to the polynucleotides of the invention, the use of hammerhead ribozymes is preferred. Hammerhead ribozymes cleave mRNAs at locations dictated by flanking regions that form complementary base pairs with the target mRNA. The sole requirement is that the target mRNA have the following sequence of two bases: 5′-UG-3′. The construction and production of hammerhead ribozymes is well known in the art and is described more fully in Haseloff and Gerlach, Nature, 334:585-591 (1988). There are numerous potential hammerhead ribozyme cleavage sites within each nucleotide sequence disclosed in the sequence listing. Preferably, the ribozyme is engineered so that the cleavage recognition site is located near the 5′ end of the mRNA corresponding to the polynucleotides of the invention; i.e., to increase efficiency and minimize the intracellular accumulation of non-functional mRNA transcripts.

As in the antisense approach, the ribozymes of the invention can be composed of modified oligonucleotides (e.g. for improved stability, targeting, etc.) and should be delivered to cells which express the polynucleotides of the invention in vivo. DNA constructs encoding the ribozyme may be introduced into the cell in the same manner as described above for the introduction of antisense encoding DNA. A preferred method of delivery involves using a DNA construct “encoding” the ribozyme under the control of a strong constitutive promoter, such as, for example, pol III or pol II promoter, so that transfected cells will produce sufficient quantities of the ribozyme to destroy endogenous messages and inhibit translation. Since ribozymes unlike antisense molecules, are catalytic, a lower intracellular concentration is required for efficiency.

Antagonist/agonist compounds may be employed to inhibit the cell growth and proliferation effects of the polypeptides of the present invention on neoplastic cells and tissues, i.e. stimulation of angiogenesis of tumors, and, therefore, retard or prevent abnormal cellular growth and proliferation, for example, in tumor formation or growth.

The antagonist/agonist may also be employed to prevent hyper-vascular diseases, and prevent the proliferation of epithelial lens cells after extracapsular cataract surgery. Prevention of the mitogenic activity of the polypeptides of the present invention may also be desirous in cases such as restenosis after balloon angioplasty.

The antagonist/agonist may also be employed to prevent the growth of scar tissue during wound healing.

The antagonist/agonist may also be employed to treat, prevent, and/or diagnose the diseases described herein.

Thus, the invention provides a method of treating or preventing diseases, disorders, and/or conditions, including but not limited to the diseases, disorders, and/or conditions listed throughout this application, associated with overexpression of a polynucleotide of the present invention by administering to a patient (a) an antisense molecule directed to the polynucleotide of the present invention, and/or (b) a ribozyme directed to the polynucleotide of the present invention.

EXAMPLES

The Examples herein are meant to exemplify the various aspects of carrying out the invention and are not intended to limit the scope of the invention in any way. The Examples do not include detailed descriptions for conventional methods employed, such as in the construction of vectors, the insertion of cDNA into such vectors, or the introduction of the resulting vectors into the appropriate host. Such methods are well known to those skilled in the art and are described in numerous publications, for example, Sambrook, Fritsch, and Maniatis, Molecular Cloning: A Laboratory Manual, 2^(nd) Edition, Cold Spring Harbor Laboratory Press, USA, (1989).

Example 1 Methods IC₅₀ Determination—In Vitro Cytotoxicity Assay

The protein tyrosine kinase inhibitor compound (described in international application WO 00/62778, published Oct. 26, 2000) was tested for cytotoxicity in vitro against a panel of twenty-three human breast cell lines available from the American Type Culture Collection, ATCC, except H3396, which was obtained from Pacific Northwest Research Institute, Seattle Wash. The MCF7/Her2 cell line was established by stable transfection of MCF7 cells with the HER2 gene. Cytotoxicity was assessed in cells by the MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulphenyl)-2H-tetrazolium, inner salt) assay (T. L. Riss et al., 1992, Mol. Biol. Cell, 3 (Suppl.):184a).

To carry out the assays, the breast cells were plated at 4,000 cells/well in 96 well microtiter plates, and 24 hours later, serially diluted drugs were added. The concentration range for the protein tyrosine kinase inhibitor compound BMS-A used in the cytotoxicity assay was from 5 μg/ml to 0.0016 μg/ml (roughly 10 μM to 0.0032 μM).

The cells were incubated at 37° C. for 72 hours at which time the tetrazolium dye, MTS (333 μg/ml final concentration), in combination with the electron coupling agent phenazine methosulfate (25 μM final concentration), was added. A dehydrogenase enzyme in live cells reduces the MTS to a form that absorbs light and can be quantified spectrophotometrically at 492 nM. The greater the absorbency the greater the number of live cells. The results are expressed as an IC₅₀, which is the drug concentration required to inhibit cell proliferation (i.e. absorbance at 492 nM) to 50% of that of untreated control cells. The mean IC₅₀ and standard deviation (SD) from multiple tests for each cell line were calculated.

Resistant/Sensitivity Classification

The IC₅₀ of the BMS-A protein tyrosine kinase inhibitor compound for each cell line was log-transformed to log₁₀(IC₅₀), and the mean log₁₀(IC₅₀) across the 23 human breast cell lines was calculated. The resistance/sensitivity phenotype of the cell lines was classified as follows: the cell lines with log₁₀(IC₅₀) below the mean log₁₀(IC₅₀) of all 23 cell lines were defined as sensitive to the compound, while those with log₁₀(IC₅₀) above the mean log₁₀(IC₅₀) were considered to be resistant to the compound. The resistance/sensitivity classification is shown in Table 1 and 7 cell lines classified as sensitive and 16 cell lines classified as resistant to the protein tyrosine kinase inhibitor compound BMS-A.

Polynucleotide Expression Profiling

The breast cells were grown under standard cell culture conditions: RPMI 1640 supplemented to contain 10% fetal bovine serum, 100 IU/ml penicillin, 100 mg/ml streptomycin, 2 mM L-glutamine and 10 mM Hepes (all from GibcoBRL, Rockville, Md.). RNA was isolated from the cultured cells, either treated or untreated with drug (i.e., the protein tyrosine kinase inhibitor compound) at 50-70% confluence using the RNeasy™ kits commercially available from Qiagen, Valencia, Calif. The quality of the RNA was assessed by measuring the 28s:18s ribosomal RNA ratio using an Agilent 2100 bioanalyzer (Agilent Technologies, Rockville, Md.). The concentration of total RNA was determined spectrophotometrically. 10 μg of total RNA from each cell line was used to prepare biotinylated probe according to the Affymetrix Genechip® Expression Analysis Technical Manual, 2001. Targets were hybridized to Affymetrix high density oligonucleotide array human HG-U133 set chips (Affymetrix, Santa Clara, Calif.). The arrays were then washed and stained using the GeneChip® Fluidics station according to the manufacture's instructions (Affymetrix Genechip® Technical Manual, 2001). The HG-U133 set contains 2 Genechip® arrays, which contain approximately 45,000 probe sets representing more than 39,000 transcripts derived from approximately 33,000 well-substantiated human polynucleotides.

Preprocessing of Microarray Data

Scanned image files were visually inspected for artifacts and analyzed with GeneChip® Expression Analysis software MAS 5.0 (Affymetrix, Santa Clara, Calif.). The “Detection Call” (Affymetrix Genechip® Expression Analysis Technical Manual, 2001) is used to determine whether a transcript is detected within one sample; the “Signal” (Affymetrix Genechip® Expression Analysis Technical Manual, 2001) measures the relative abundance of a transcript. The trimmed mean intensity for each chip was scaled to 1,500 (see, Affymetrix Genechip® Expression Analysis Technical Manual, 2001) in order to account for any minor differences in global chip intensity, so that the overall expression level for each cell line was comparable. Affymetrix control sequences were removed prior to analysis.

Of a total of 44,792 probe sets on the HG-U133 arrays, 15,707 represented probe sets were not detected (Absent Call; p-value>0.06) across all of the 23 breast cell lines using the Affymetrix GeneChip® Expression Analysis algorithm; these undetected polynucleotides were excluded from further analysis.

The remaining data containing 29,085 probe sets were transferred to the GeneCluster software (Whitehead Institute; T. R. Golub et al., 1999, Science, 286:531-537). A threshold filter was applied to the polynucleotide expression values of the remaining data to remove low and high polynucleotide expression values that were not likely to be in the linear range of the Affymetrix fluorescent scanner. The threshold filter converted all polynucleotide expression values that were below 100 units to 100 units, and all polynucleotide expression values that were above 45,000 units to 45,000 units. All represented polynucleotides whose polynucleotide expression values were between 100 and 45,000 were not changed.

A second “variation filter” was then applied to the data set to find polynucleotides that were likely to correlate with different properties and features of the 23 cell lines. The object of the second filter was to select those polynucleotides whose expression pattern varied across the data set, because a polynucleotide that does not vary can not provide information about differing properties of the 23 cell line panel. For example, if there are two populations of cells within the data set, e.g., fast growing cells and slow growing cells, then a polynucleotide whose expression is constant, or whose expression does not change substantially, can not yield information that would correlate to fast or slow cell growth.

The second variation filter was formulated to determine the expression pattern of each polynucleotide across the 23 breast cell lines and to find polynucleotides that passed the following criteria:

-   -   1. The polynucleotide must show a three-fold change in absolute         expression, i.e., as depicted in the formula:

$\frac{{expression}\mspace{14mu}{value}\mspace{14mu}{in}\mspace{14mu}{any}\mspace{14mu}{given}\mspace{14mu}{cell}\mspace{14mu}{line}}{{expression}\mspace{14mu}{value}\mspace{14mu}{in}\mspace{14mu}{any}\mspace{14mu}{other}\mspace{14mu}{cell}\mspace{14mu}{line}} > {3\mspace{14mu}{or}} < 0.33$

-   -   2. In addition to 1, the three-fold change must represent an         absolute difference of 1000 expression units.     -   3. In addition, the criteria in #1 and #2 above must be met on         four independent occasions within the data set, i.e., Cell line         A/B, Cell line E/F, Cell line C/U and Cell line T/G. (The         algorithm does not use a single expression value for one cell         line on multiple occasions, i.e., Cell Line A/B, Cell line A/G,         Cell line A/F and Cell line B/F).

The second variation filter reduced the data set to 5322 polynucleotides. After the second variation filter, the expression value for each polynucleotide was log transformed and normalized to the mean across all of the 23 samples (mean set to 0 and standard deviation set to 1). This normalized data set was used to select polynucleotides which significantly correlated with the property of sensitivity toward a drug class as described herein.

Drug (BMS-A) Treatment of Breast Cell Lines and Selection of Polynucleotides Modified by the Drug

The 11 breast cell lines (indicated in bold in the Table 1) with an IC₅₀ ranging from 0.0055 to 9.5 μM were used in a drug induction study employing the BMS-A protein tyrosine kinase inhibitor. Cells were seeded in a 10 cm² culture plate in cell culture medium as described herein and were cultured for 24 hours at 37° C. The medium was then changed to medium containing drug (0.4 μM BMS-A compound in 0.1% DMSO, Sigma); the cells were incubated for another 24 hours, and then lysed for RNA isolation. The expression profiling was performed as described above and data were analyzed using GeneChip® Expression Analysis software MAS 5.0 (Affymetrix, Santa Clara, Calif.). The expression data of a drug treated cell line were compared pair-wise to data from the same cell line untreated with drug. A change in p-value was calculated, indicating an increase, decrease or no change in polynucleotide expression. When the p-value was less than 0.0025, the change was considered to be significant. This analysis was performed for all 11 cell lines to compare the polynucleotide expression with or without drug treatment.

Example 2 PCR Expression Profiling

RNA quantification is performed using the Taqman® real-time-PCR fluorogenic assay. The Taqman® assay is one of the most precise methods for assaying the concentration of nucleic acid templates.

RNA is prepared using standard methods, preferably, employing the RNeasy Maxi Kit commercially available from Qiagen (Valencia, Calif.). A cDNA template for real-time PCR can be generated using the Superscript™ First Strand Synthesis system for RT-PCR. Representative forward and reverse RT-PCT primers for each of the protein tyrosine kinase biomarker polynucleotides of the present invention are provided in Table 6.

SYBR Green real-time PCR reactions are prepared as follows: The reaction mix contains 20 ng first strand cDNA; 50 nM Forward Primer; 50 nM Reverse Primer; 0.75×SYBR Green I (Sigma); 1×SYBR Green PCR Buffer (50 mM Tris-HCl pH 8.3, 75 mM KCl); 10% DMSO; 3 mM MgCl₂; 300 μM each dATP, dGTP, dTTP, dCTP; 1 U Platinum® Taq DNA Polymerase High Fidelity (Cat# 11304-029; Life Technologies; Rockville, Md.). Real-time PCR is performed using an Applied Biosystems 5700 Sequence Detection System. Conditions are 95° C. for 10 minutes (denaturation and activation of Platinum® Taq DNA Polymerase), 40 cycles of PCR (95° C. for 15 seconds, 60° C. for 1 minute). PCR products are analyzed for uniform melting using an analysis algorithm built into the 5700 Sequence Detection System.

cDNA quantification used in the normalization of template quantity is performed using Taqman® technology. Taqman® reactions are prepared as follows: The reaction mix comprises 20 ng first strand cDNA; 25 nM GAPDH-F3, Forward Primer; 250 nM GAPDH-R1 Reverse Primer; 200 nM GAPDH-PVIC Taqman® Probe (fluorescent dye labeled oligonucleotide primer); 1× Buffer A (Applied Biosystems); 5.5 mM MgCl₂; 300 μM dATP, dGTP, dTTP, dCTP; and 1 U Amplitaq Gold (Applied Biosystems). GAPDH (D-glyceraldehyde-3-phosphate dehydrogenase) is used as a control to normalize mRNA levels. Real-time Taqman® PCR is performed using an Applied Biosystems 7700 Sequence Detection System. Conditions are 95° C. for 10 minutes (denaturation and activation of Amplitaq Gold), 40 cycles of PCR (95° C. for 15 seconds, 60° C. for 1 minute).

The sequences for the GAPDH oligonucleotides used in the Taqman® reactions are as follows:

(SEQ ID NO:531) GAPDH-F3: 5′-AGCCGAGCCACATCGCT-3′; (SEQ ID NO:532) GAPDH-R1: 5′-GTGACCAGGCGCCCAATAC-3′; and (SEQ ID NO:533) GAPDH-PVIC Taqman ® Probe - VIC-5′- CAAATCCGTTGACTCCGACCTTCACCTT-3′ TAMRA.

The Sequence Detection System generates a Ct (threshold cycle) value that is used to calculate a concentration for each input cDNA template. cDNA levels for each polynucleotide of interest are normalized to GAPDH cDNA levels to compensate for variations in total cDNA quantity in the input sample. This is done by generating GAPDH Ct values for each cell line. Ct values for the polynucleotide of interest and GAPDH are inserted into a modified version of the δδCt equation (Applied Biosystems Prism® 7700 Sequence Detection System User Bulletin #2), which is used to calculate a GAPDH normalized relative cDNA level for each specific cDNA. The δδCt equation is as follows: relative quantity of nucleic acid template=2^(δδCt)=2^((δCta-δCtb)), where δCta=Ct target−Ct GAPDH, and δCtb=Ct reference−Ct GAPDH. (No reference cell line is used for the calculation of relative quantity; δCtb is defined as 21).

Example 3 Production of an Antibody Directed Against Protein Tyrosine Kinase Biomarker Polypeptides

Anti-protein tyrosine kinase biomarker polypeptide antibodies of the present invention can be prepared by a variety of methods as detailed hereinabove. As one example of an antibody-production method, cells expressing a polypeptide of the present invention are administered to an animal as immunogen to induce the production of sera containing polyclonal antibodies directed against the expressed polypeptide. In a preferred method, the expressed polypeptide is prepared, preferably isolated and/or purified, to render it substantially free of natural contaminants using techniques commonly practiced in the art. Such a preparation is then introduced into an animal in order to produce polyclonal antisera of greater specific activity for the expressed and isolated polypeptide.

In a most preferred method, the antibodies of the present invention are monoclonal antibodies (or protein binding fragments thereof) and can be prepared using hybridoma technology as detailed hereinabove. Cells expressing the polypeptide can be cultured in any suitable tissue culture medium; however, it is frequently preferable to culture cells in Earle's modified Eagle's medium supplemented to contain 10% fetal bovine serum (inactivated at about 56° C.), and supplemented to contain about 10 g/l nonessential amino acids, about 1.0 U/ml penicillin, and about 100 μg/ml streptomycin.

The splenocytes of immunized (and boosted) mice are extracted and fused with a suitable myeloma cell line. Any suitable myeloma cell line can be employed in accordance with the present invention; however, it is preferable to employ the parent myeloma cell line SP2/0, available from the ATCC. After fusion, the resulting hybridoma cells are selectively maintained in HAT medium, and then cloned by limiting dilution as described, for example, by Wands et al. (1981, Gastroenterology, 80:225-232). The hybridoma cells obtained through such a selection process are then assayed to identify those cell clones that secrete antibodies capable of binding to the polypeptide immunogen, or a portion thereof.

Alternatively, additional antibodies capable of binding to the polypeptide can be produced in a two-step procedure using anti-idiotypic antibodies. Such a method makes use of the fact that antibodies are themselves antigens, and therefore, it is possible to obtain a second antibody that binds to a first antibody. In accordance with this method, protein-specific antibodies are used to immunize an animal, preferably a mouse. The splenocytes of such an immunized animal are then used to produce hybridoma cells, and the hybridoma cells are screened to identify clones that produce an antibody whose ability to bind to the protein-specific antibodies can be blocked by the protein. Such antibodies comprise anti-idiotypic antibodies to the protein-specific antibody and can be used to immunize an animal to induce the formation of further protein-specific antibodies.

For in vivo use of antibodies in humans, it may be preferable to use “humanized” chimeric monoclonal antibodies. Such antibodies can be produced using genetic constructs derived from hybridoma cells producing the monoclonal antibodies described above. Methods for producing chimeric antibodies are known and practiced in the art. (See, e.g., for review, Morrison, 1985, Science, 229:1202); Oi et al., 1986, BioTechniques, 4:214; Cabilly et al., U.S. Pat. No. 4,816,567; Taniguchi et al., EP 171496; Morrison et al., EP 173494; Neuberger et al., WO 8601533; Robinson et al., WO 8702671; Boulianne et al., 1984, Nature, 312:643; and Neuberger et al., 1985, Nature, 314:268).

Example 4 Immunofluorescence Assays

The following immunofluorescence protocol can be used, for example, to verify protein tyrosine kinase biomarker expression in cells, or, for example, to check for the presence of one or more antibodies that bind protein tyrosine kinase biomarkers (polypeptides or peptides) expressed on the surfaces of cells. Briefly, Lab-Tek II chamber slides are coated overnight at 4° C. with 10 μg/ml of bovine collagen Type II in DPBS containing calcium and magnesium (DPBS++). The slides are then washed twice with cold DPBS++ and seeded with approximately 8000 CHO cells transfected with a vector comprising the coding sequence for a protein tyrosine kinase biomarker of the present invention or with CHO cells transfected with vector alone (control) in a total volume of 125 μl and incubated at 37° C. in the presence of 95% oxygen/5% carbon dioxide.

Thereafter, the culture medium is gently removed by aspiration and the adherent cells are washed twice with DPBS++ at ambient temperature. The slides are blocked with DPBS++ containing 0.2% BSA (blocker) at 0-4° C. for one hour. The blocking solution is gently removed by aspiration, and 125 μl of antibody containing solution (an antibody containing solution may be, for example, a hybridoma culture supernatant which is usually used undiluted, or serum/plasma which is usually diluted, e.g., a dilution of about 1:50, 1:100, 1:1000, and the like). The slides are incubated for 1 hour at 0-4° C. Antibody solutions are then gently removed by aspiration and the cells are washed 5 times with 400 μl of ice cold blocking solution. Next, 125 μl of 1 μg/ml rhodamine labeled secondary antibody (e.g., anti-human IgG) in blocker solution is added to the cells. Again, cells are incubated for 1 hour at 0-4° C.

The secondary antibody solution is then gently removed by aspiration and the cells are washed 3 times with 400 μl of ice cold blocking solution, and 5 times with cold DPBS++. The cells are then fixed with 125 μl of 3.7% formaldehyde in DPBS++ for 15 minutes at ambient temperature. Thereafter, the cells are washed 5 times with 400 μl of DPBS++ at ambient temperature. Finally, the cells are mounted in 50% aqueous glycerol and viewed using a fluorescence microscope using rhodamine filters.

Example 5 Complimentary Sequences

Antisense molecules or nucleic acid sequences complementary to the protein tyrosine kinase biomarker polypeptides-encoding sequence, or any part thereof, is used to decrease or to inhibit the expression of naturally occurring protein tyrosine kinase biomarker polypeptides. Although the use of antisense or complementary oligonucleotides comprising about 15 to 35 base-pairs is described, essentially the same procedure is used with smaller or larger nucleic acid sequence fragments. An oligonucleotide based on the coding sequence of protein tyrosine kinase biomarker polypeptides, as depicted in SEQ ID NO:1 thru 137, for example, is used to inhibit expression of naturally occurring protein tyrosine kinase biomarker polypeptides. The complementary oligonucleotide is typically designed from the most unique 5′ sequence and is used either to inhibit transcription by preventing promoter binding to the coding sequence, or to inhibit translation by preventing the ribosome from binding to the protein tyrosine kinase biomarker polypeptides-encoding transcript, among others. However, other regions may also be targeted.

Using an appropriate portion of the signal and 5′ sequence of SEQ ID NO:1 thru 137, an effective antisense oligonucleotide includes any of about 15-35 nucleotides spanning the region which translates into the signal or 5′ coding sequence, among other regions, of the polypeptide as depicted in SEQ ID NO:138 thru 256. Appropriate oligonucleotides may be designed using OLIGO 4.06 software and the protein tyrosine kinase biomarker polypeptides coding sequence (SEQ ID NO:1 thru 137). Preferred oligonucleotides are deoxynucleotide, or chimeric deoxynucleotide/ribonucleotide based and are provided below. The oligonucleotides may be synthesized using chemistry essentially as described in U.S. Pat. No. 5,849,902; which is hereby incorporated herein by reference in its entirety.

Representative RNAi reagent sequences are as follows:

SEQ SEQ ID ID Target Name Sense Strand RNAi Reagent NO; Anti-Sense Strand RNAi Reagent NO: caveolin 1-1 CAGGGCAACAUCUACAAGCTT 534 GCUUGUAGAUGUUGCCCUGTT 5546 caveolin 1-2 GCAAGUGUACGACGCGCACTT 5535 GUGCGCGUCGUACACUUGCTT 5547 caveolin 1-3 CCGCUUGCUGUCUGCCCUCTT 5536 GAGGGCAGACAGCAAGCGGTT 5548 caveolin 1-4 CAUCUGGGCAGUUGUACCATT 5537 UGGUACAACUGCCCAGAUGTT 5549 caveolin 2-1 CUACGCACUCCUUUGACAATT 5538 UUGUCAAAGGAGUGCGUAGTT 5550 caveolin 2-2 AGUGUGGAUCUGCAGCCAUTT 5539 AUGGCUGCAGAUCCACACUTT 5551 caveolin 2-3 GUUCCUGACGGUGUUCCUGTT 5540 CAGGAACACCGUCAGGAACTT 5552 caveolin 2-4 UUGCGGGAAUUCUCUUUGCTT 5541 GCAAAGAGAAUUCCCGCAATT 5553 ephA2-1 GGAAGUGGUACUGCUGGACTT 5542 GUCCAGCAGUACCACUUCCTT 5554 ephA2-2 CUUCCAGAAGCGCCUGUUCTT 5543 GAACAGGCGCUUCUGGAAGTT 5555 ephA2-3 GAGCCCCGUAUGCACUGUGTT 5544 CACAGUGCAUACGGGGCUCTT 5556 ephA2-4 CUACACCUUCACCGUGGAGTT 5545 CUCCACGGUGAAGGUGUAGTT 5557

Transfection of Post-Quiescent A549 Cells with AntiSense Oligonucleotides

Materials needed:

-   -   A549 cells can be maintained in DMEM with high glucose         (Gibco-BRL) supplemented with 10% Fetal Bovine Serum, 2 mM         L-Glutamine, and 1× penicillin/streptomycin.     -   Opti-MEM (Gibco-BRL)     -   Lipofectamine 2000 (Invitrogen)     -   Antisense oligomers (Qiagen)     -   Polystyrene tubes.     -   Tissue culture treated plates.

Quiescent cells are prepared as follows:

-   Day 0: 300,000 A549 cells are seeded in a T75 tissue culture flask     in 10 ml of A549 media (as specified above), and incubated in at 37°     C., 5% CO₂ in a humidified incubator for 48 hours. -   Day 2: The T75 flasks are rocked to remove any loosely adherent     cells, and the A549 growth media removed and replenished with 10 ml     of fresh A549 media. The cells are cultured for six days without     changing the media to create a quiescent cell population. -   Day 8: Quiescent cells are plated in multi-well format and     transfected with antisense oligonucleotides.

A549 cells are transfected according to the following:

-   -   1. Trypsinize T75 flask containing quiescent population of A549         cells.     -   2. Count the cells and seed 24-well plates with 60K quiescent         A549 cells per well.     -   3. Allow the cells to adhere to the tissue culture plate         (approximately 4 hours).     -   4. Transfect the cells with antisense and control         oligonucleotides according to the following:         -   a. A 10× stock of lipofectamine 2000 (10 ug/ml is 10×) may             be prepared, and diluted lipid is allowed to stand at RT for             15 minutes.         -   Stock solution of lipofectamine 2000 is 1 mg/ml.         -   10× solution for transfection is 10 ug/ml.         -   To prepare 10× solution, dilute 10 ul of lipofectamine 2000             stock per 1 ml of Opti-MEM (serum free media).         -   b. A 10× stock of each oligomer may be prepared for use in             the transfection.         -   Stock solutions of oligomers are at 100 uM in 20 mM HEPES,             pH 7.5.         -   10× concentration of oligomer may be 0.25 uM.         -   To prepare the 10× solutions, dilute 2.5 ul of oligomer per             1 ml of Opti-MEM.         -   c. Equal volumes of the 10× lipofectamine 2000 stock and the             10× oligomer solutions are mixed well, and incubated for 15             minutes at RT to allow complexation of the oligomer and             lipid. The resulting mixture is 5×.         -   d. After the 15 minute complexation, 4 volumes of full             growth media is added to the oligomer/lipid complexes             (solution may be 1×).         -   e. The media may be aspirated from the cells, and 0.5 ml of             the 1× oligomer/lipid complexes added to each well.         -   f. The cells are incubated for 16-24 hours at 37° C. in a             humidified CO₂ incubator.         -   g. Cell pellets are harvested for RNA isolation and TaqMan             analysis of the expression of the protein tyrosine kinase             biomarker polypeptides to assess level of knock-down.

TaqMan Reactions

Quantitative RT-PCR analysis may be performed on total RNA preps that are treated with DNaseI or poly A selected RNA. The Dnase treatment may be performed using methods known in the art, though preferably using a Qiagen RNeasy kit to purify the RNA samples, wherein DNAse I treatment is performed on the column.

Briefly, a master mix of reagents may be prepared according to the following table:

Dnase I Treatment

Reagent Per r'xn (in uL) 10× Buffer 2.5 Dnase I (1 unit/ul @1 unit per ug sample) 2 DEPC H₂O 0.5 RNA sample @ 0.1 ug/ul 20 (2-3 ug total) Total 25

Next, 5 ul of master mix may be aliquoted per well of a 96-well PCR reaction plate (PE part # N801-0560). RNA samples are adjusted to 0.1 ug/ul with DEPC treated H₂O (if necessary), and 20 ul may be added to the aliquoted master mix for a final reaction volume of 25 ul.

The wells are capped using strip well caps (PE part # N801-0935), placed in a plate, and briefly spun in a plate centrifuge (Beckman) to collect all volume in the bottom of the tubes. Generally, a short spin up to 500 rpm in a Sorvall RT is sufficient

The plates are incubated at 37° C. for 30 mins. Then, an equal volume of 0.1 mM EDTA in 10 mM Tris may be added to each well, and heat inactivated at 70° C. for 5 min. The plates are stored at −80° C. upon completion.

RT Reaction

A master mix of reagents may be prepared according to the following table:

RT Reaction

RT No RT Reagent Per Rx'n (in ul) Per Rx'n (in ul) 10× RT buffer 5 2.5 MgCl₂ 11 5.5 DNTP mixture 10 5 Random Hexamers 2.5 1.25 Rnase inhibitors 1.25 0.625 RT enzyme 1.25 — Total RNA 500 ng (100 ng no RT) 19.0 max 10.125 max DEPC H₂O — — Total 50 uL 25 uL

Samples are adjusted to a concentration so that 500 ng of RNA is added to each RT rx′n (100 ng for the no RT). A maximum of 19 ul can be added to the RT rx′n mixture (10.125 ul for the no RT.) Any remaining volume up to the maximum values may be filled with DEPC treated H₂O, so that the total reaction volume is 50 ul (RT) or 25 ul (no RT).

On a 96-well PCR reaction plate (PE part # N801-0560), 37.5 ul of master mix may be aliquoted (22.5 ul of no RT master mix), and the RNA sample added for a total reaction volume of 50 ul (25 ul, no RT). Control samples are loaded into two or even three different wells in order to have enough template for generation of a standard curve.

The wells are capped using strip well caps (PE part # N801-0935), placed in a plate, and spin briefly in a plate centrifuge (Beckman) to collect all volume in the bottom of the tubes. Generally, a short spin up to 500 rpm in a Sorvall RT is sufficient.

For the RT-PCR reaction, the following thermal profile may be used:

-   -   25° C. for 10 min     -   48° C. for 30 min     -   95° C. for 5 min     -   4° C. hold (for 1 hour)     -   Store plate @−20° C. or lower upon completion.

TaqMan Reaction (Template Comes from RT Plate)

A master mix may be prepared according to the following table:

TaqMan Reaction (Per Well)

Reagent Per Rx'n (in ul) TaqMan Master Mix 4.17 100 uM Probe .025 100 uM Forward primer .05 100 uM Reverse primer .05 Template — DEPC H₂O 18.21 Total 22.5

Appropriate forward, reverse, and probe primers may be designed for each protein tyrosine kinase biomarker polypeptides coding region for use in the RT-PCR reaction

Using a Gilson P-10 repeat pipetter, 22.5 ul of master mix is aliquouted per well of a 96-well optical plate. Then, using P-10 pipetter, 2.5 ul of sample is added to individual wells. Generally, RT samples are run in triplicate with each primer/probe set used, and no RT samples are run once and only with one primer/probe set, often gapdh (or other internal control).

A standard curve is then constructed and loaded onto the plate. The curve has five points plus one no template control (NTC, =DEPC treated H₂O). The curve may be made with a high point of 50 ng of sample (twice the amount of RNA in unknowns), and successive samples of 25, 10, 5, and 1 ng. The curve may be made from a control sample(s) (see above).

The wells are capped using optical strip well caps (PE part # N801-0935), placed in a plate, and spun in a centrifuge to collect all volume in the bottom of the tubes. Generally, a short spin up to 500 rpm in a Sorvall RT is sufficient.

Plates are loaded onto a PE 5700 sequence detector making sure the plate is aligned properly with the notch in the upper right hand corner. The lid may be tightened down and run using the 5700 and 5700 quantitation program and the SYBR probe using the following thermal profile:

-   -   50° C. for 2 min     -   95° C. for 10 min     -   and the following for 40 cycles:         -   95° C. for 15 sec         -   60° C. for 1 min     -   Change the reaction volume to 25 ul.

Once the reaction may be complete, a manual threshold of around 0.1 may be set to minimize the background signal. Additional information relative to operation of the GeneAmp 5700 machine may be found in reference to the following manuals: “GeneAmp 5700 Sequence Detection System Operator Training CD”; and the “User's Manual for 5700 Sequence Detection System”; available from Perkin-Elmer and hereby incorporated by reference herein in their entirety.

The skilled artisan would acknowledge that modifications to the above protocol may be required for each protein tyrosine kinase biomarker polypeptide of the present invention. The skilled artisan would also acknowledge that cell lines other than A549 could be used and that A549 are only provided as an example. The skilled artisan would also acknowledge that other means may be used to assess the ability of a complimentary oligonucleotide, such as the RNAi reagents provided in SEQ ID NO:534 to 557, which include, but are not limited to western blots and ELISA assays, among others.

Example 6 Alternative Method of Assessing Ability of Complimentary Sequences to Modulate Expression Levels of the Protein Tyrosine Kinase Biomarker Polypeptides of the Present Invention

Preferred complimentary sequences that may be assessed for their ability to modulate the expression levels the protein tyrosine kinase biomarker polypeptides of the present invention are provided as SEQ ID NO:534 to 557. Other complimentary sequences may be designed based upon the coding region of the protein tyrosine kinase biomarker polypeptides of the present invention as provided as SEQ ID NO:1 thru 137, and are specifically contemplated by the present invention.

Co-Transfection RNAi

Transfection:

Day prior to transfection, seed 2×10⁵ HeLa cells per well of a 24 well dish. The following day, cells should be 90-95% confluent. Dilute 4.5 uL of 20 uM stock RNAi (one or more of SEQ ID NO:534 to 557) in 50 uL Optimem in a polystyrene tube for each RNAi to be transfected (tube A). Mix by gentle tapping. In another polystyrene tube combine 2 uL Lipofectamine 2000 with 50 uL Optimem (tube B). Mix by gentle tapping. Allow to sit at RT for 5′. Combine 50 uL tube B with the 50 uL for each tube A. Mix by gentle tapping. Allow to sit at RT for 15′. Add 500 uL serum/antibiotic-free MEM to each tube to give a final RNAi concentration of 150 nM. (For cotransfections of RNAi with plasmid, use 1 uL of 20 uM stock RNAi (final concentration of 33 nM) along with 1 ug vector DNA in tube A, and then proceed with transfection protocol above). Remove the media from HeLa plates and replace with the 600 uL transfection mix. Put in 37° C. 5% CO₂ incubator for 4-5 hours. Replace the media with MEM containing 10% FBS.

Controls to include in the transfection include a fluorescent oligonucleotide control (1 U/uL=20 uM) to calculate transfection efficiency, GFP B as a non-specific negative control, CDC2 as a normalizing knockdown control, and an untransfected control receiving no DNA.

Lysis:

48 hours post-transfection, aspirate media and wash cells 1× with approx. 500 uL cold 1×PBS per well. Aspirate and replace with 100 uL cold RIPA containing protease inhibitors (1 mini BM protease inhibitor tablet/10 mL 1×RIPA). Rock and tap the plate a few times and place at 4° C. for 10-15 minutes. Tap/rock the plate several more times. Using a 200 uL pipetteman, aspirate 5-10 times and wash the well to ensure complete lysis and transfer of all material. Transfer lysate to an eppendorf tube and pipette up and down 5-10 times. If sample is still viscous, pipette up and down several more times. Spin samples down for 10′ at 14000 RPM 4° C. Samples can now be stored at −20° C. or prepared for loading.

Western Blotting/Novex:

Prepare sample by combining 20 uL lysate with 3 uL reducing reagent and 7 uL 4× gel loading dye. Heat at 70° C. for 10′ and then place samples on ice. While samples are heating, prepare desired gel (usually a 4-12% Bis-Tris gel) by removing comb and sealing tape. Place gels in gel box and fill inner and outer chambers with desired buffer (either 1×MES or MOPS— Add 50 mL 20× buffer to 950 mL dH20 for each gel box). Add 600 uL Oxidizing reagent to the inner chamber. Wash out each well by blasting with 500 uL buffer. In well one, load 5 uL marker—Invitrogen's SeeBlue Plus2. Load samples in subsequent lanes. Run gel at 200V for 45-50 minutes. Make up 1× transfer buffer-50 mL 20× transfer buffer, Methanol (100 mL if transferring one gel, 200 mL if transferring 2 gels in the same apparatus) and dH20 to 1000 mL. Soak blotting pads in dH20 and then transfer buffer—make sure to push down on pads to rid of air bubbles. Soak precut Hybond-ECL membrane (Amersham nitrocellulose) in dH20 and then in transfer buffer. Cut the end off of Biorad filter paper to match size of transfer membrane. If transferring one gel, place 2 blotting pads into blotting chamber. For 2 gels, place down 1 pad. Briefly soak a filter paper in transfer buffer and carefully lay on blotting pad. Open gel cassette with cracking tool, cut off top, bottom and sides of gel. Briefly rinse it in transfer buffer and then lay it on filter paper carefully making sure no air bubbles are present. Lay transfer membrane on top again being careful there are no bubbles. Put down filter paper. Put down 2 blotting pads if transferring one gel to complete the sandwich. If transferring 2, put down 1 blotting pad, filter paper, gel, membrane, filter paper, blotting pad. Gels are now ready for transfer. Squeeze together the gel sandwich and place in transfer apparatus. Fill inner and outer chambers with transfer buffers. Transfer gels for 1 hour at 30V.

Remove membranes and place them in Superblock (Pierce) and rock at RT for a minimum of 1 hour-overnight. (I have stored membranes in Superblock at 4° C. over the weekend). Primary antibody and normalizing antibody are diluted in a 1:10 mix of Superblock: 1×PBS/0.3% Tween-20. Membranes are incubated and rocked at RT in primary antibody for a minimum of 1 hour-overnight. Membranes are then washed thoroughly in 1×PBS/0.3% Tween-20. I usually give several quick rinses and then rinse 3×5′ in 1×PBS/0.3% Tween-20. During the final wash, HRP-conjugated secondary antibody is diluted in 1×PBS/0.3% Tween-20. Add this to membrane and rock at RT for a minimum of 30′. Wash membranes thoroughly. I usually give several quick rinses and then rinse 3×5′ in 1×PBS/0.3% Tween-20. Membranes are removed from wash buffer and the excess buffer drained by holding the edge of the membranes on a paper towel. Membranes are placed on Saran Wrap that has been smoothed on benchtop to remove air bubbles. Enough ECL reagent is added to cover the membrane for 1 minute. Remove membranes and drain off excess ECL on paper towel. Place membranes in between two transparency sheets, being careful to smooth out air bubbles.

Quantitation:

Expose membranes using Fluor S-Max. Relative percent inhibition may be determined by comparing the intensity of each band with RNAi treatment to the intensity of each band without RNAi treatment (control). Normalize lanes by dividing band of interest by normalizing band for each lane. Divide the normalized value for each treated sample by the normalized value of the control. Percent inhibition can then be calculated by using the formula (1-above value)×100.

The skilled artisan would acknowledge that modifications to the above protocol may be required for each protein tyrosine kinase biomarker polypeptide of the present invention.

Example 6 Method of Further Assessing the Prediction Accuracy of the Predictor Polynucleotides and Polypeptides by Testing 12 Additional Breast Cancer Cell Lines

The ability of the 137 predictor polynucleotides and polypeptides of the present invention to predict which cell lines are sensitive or resistant to compound BMS-A was further evaluated by testing 12 new breast cancer cell lines that were never used in the identification of these polynucleotides. Assays were performed as described in Example 1 herein.

As demonstrated in Table 7, the IC₅₀ for each of 12 new breast cancer cell lines to BMS-A was measured and the resistance/sensitivity phenotype classification of the 12 new breast cancer cell lines was based on their IC₅₀ results. The cell lines with a IC₅₀ below 1 μM were defined as sensitive to the compound, while those having a IC₅₀ above 1 μM were considered to be resistant. The gene expression profiling for the 12 breast cancer cell lines was performed using Affymetrix gene chip Hu-U133 sets as described in Example 1.

The results of these experiments are summarized in Table 7 and described herein.

Based on biological function of the markers shown in Table 2 in relation to protein tyrosine kinases, especially src-family kinase related signaling pathways and based on changes of their expression level modulated by BMS-A treatment, six polynucleotides as listed in Table 8 were selected to comprise a predictor set that was then utilized to make prediction on the additional 12 breast cell lines described above.

The results for the six polynuclelotide predictor set is summarized in Tables 9 and 10 and described herein.

Example 7 Method of Further Assessing the Prediction Accuracy of the Predictor Polynucleotides and Polypeptides by Testing 23 Lung Cancer Cell Lines

Although the polynucleotides listed in Table 2 were identified from breast cancer cell lines and their ability to identify breast cancer cell lines that are sensitive or resistant to compound BMS-A demonstrated, an investigation was made to assess these polynucleotides ability to identify sensitive or resistant cell lines to compound BMS-A in another tissue type—namely lung cancer cell lines.

The resistance/sensitivity phenotype classification of the 23 lung cancer cell lines for BMS-A based on their IC₅₀ results was assessed using the same method described in Example 1 herein. The cell lines with a IC₅₀ below 1 μM were defined as sensitive to the compound, while those having a IC₅₀ above 1 μM were considered to be resistant.

The results of this experiment are summarized in Table 11 and described elsewhere herein.

An additional investigation was made to further assess the ability of the six predictor polynucleotides listed in Table 8 to identify lung cancer cell lines that are sensitive or resistant to compound BMS-A. The same method described in Example 1 and the present example was utilized.

The results of this experiment are summarized in Table 12 and described elsewhere herein.

Example 8 Method of Demonstrating Inhibition of SRC Expression by Antisense Results in Decreased Expression of Predictor Polynucleotides and Polypeptides of the Present Invention as Shown by RT-PCR Assays

Markers, such as EphA2 and caveolin are shown to be down regulated by BMS-A drug treatment (FIG. 2) through inhibition of the activity of protein tyrosine kinases, such as Src and Src-family kinase. Antisense experiments to block Src expression were performed to see whether it has the same effects on expression of the markers. In the antisense experiment as shown in FIG. 8, two negative control antisense (NC-AS) oligos (NC-18029 and NC-18030) or three Src specific antisense (Src-AS) oilgos (Src-AS-18025, Src-AS-18028 and Src-AS-18032) made by Sequitur Inc. were used to transfect a lung cancer cell line A459. The transfection was done in triplicates. After 24 hours, cells from each transfection experiment were harvested for RNA preparation, which was then used in quantitative RT-PCR assays to measure the expression of Src and EphA2 genes. The expression of Src and EphA2 was normalized to the expression of GAPDH gene, and the values shown in the FIG. 8 represented the average of RT-PCR results (triplicate RT-PCR reactions for each of 3 transfection experiments of either two NC-AS oligos or three different Src-AS oligos).

Materials:

-   -   A549 cells were maintained in DMEM with high glucose (Gibco-BRL)         supplemented with 10% Fetal Bovine Serum, 2 mM L-Glutamine and         1× penicillin/streptomycin.     -   Opti-MEM (Gibco-BRL)     -   Lipofectamine 2000 (Invitrogen)     -   Polystyrene tubes     -   Tissue culture treated plates     -   Src antisense oligomers (Sequitur): src-S18025, src-S18028,         src-S18032     -   Negative control antisense oligomers (Sequitur): NC-S18029 and         NC-18030

Protocol for Transfection of A549 Cells with Antisense Oligonucleotides

-   -   1. 3×10⁴ A549 cells were seeded per well in 24-well plates         (Cells were approximately 60% confluent at start of         transfection) and cultured at 37° C. overnight.     -   2. Next day, an equal volume (50 μl) of the 10× stock of         Lipofectamine 2000 (10 μg/ml) and 10× stock of each antisense         oligomer (250 nM in Opti-MEM) solutions were combined to form a         5× mixture, mixed well, and incubated for 15 minutes at room         temperature to allow complex formation between the oligomer and         lipid.     -   3. After complex formation, 4 volumes of full growth media (400         μl) was added to the oligomer/lipid complexes to form a 1×         solution.     -   4. Media was aspirated from the cells and 500 μl of the 1×         oligomer/lipid complex was added to each well. Triplicates were         performed for each condition.     -   5. Cells were incubated at 37° C. in a humidified CO₂ incubator         for 24 hours, and harvested for RNA isolation.

Quantitative RT-PCR Assays for Antisense Transfected Cells

-   -   1. Total RNA was isolated using Qiagen RNAeasy mini-kit. Samples         were quantitated using a Beckman DU600 spectrophotometer.         Quality of total RNA was assessed using the Agilent Bioanalyzer         2100.     -   2. Reverse transcription reaction was performed using 0.5 μg of         each RNA sample and RT reagent (Applied Biosystems) in 25 ul         reactions at 25° C., 10 min., 48° C., 30 min., 95° C., 5 min.         175 μl of water was added to bring total volume to 200 ul. Then,         8 μl (20 ng) of each RNA sample was used in each subsequent PCR         reaction.     -   3. The primers for quantitative RT-PCR are listed below for the         predictor polynucleotides assayed.

Primer Sequences

GAPDH(Genosys): Forward- AGCCGAGCCACATCGCT (SEQ ID NO:531) Reverse- GTGACCAGGCGCCCAATAC (SEQ ID NO:532) Src (Invitrogen): Forward- AAGCCTGGCACGATGTCT (SEQ ID NO:562) Reverse- TCTGAAACCACAGCATACAACTG (SEQ ID NO:563) Caveolin1 (Invitrogen): Forward- ACAAGTTCCTGACGGTGTTCCT (SEQ ID NO:564) Reverse- GCAGAACCATTAGGCAGGTCTT (SEQ ID NO:565) Caveolin2 (Invitrogen): Forward- GATCGCAGAGCCGGTGACTA (SEQ ID NO:566) Reverse- GGAACACCGTCAGGAACTTGTAC (SEQ ID NO:567) EphA2 (Invitrogen): Forward- CCAGTTCAGCCACCACAACAT (SEQ ID NO:568) Reverse- TTCTCCCGAAGGAACTTGTCC (SEQ ID NO:569) EphB2 (Invitrogen): Forward- GGCTGTGAACGGCGTTACTG (SEQ ID NO:571) Reverse- GGTGCGGCTCACCTGATG (SEQ ID NO:572)

-   -   1. PCR reactions were performed using the SYBR Green Master Mix         (2×), Forward and Reverse primers at final concentration of 0.5         μM, and 8 μl (20 ng) of RT reaction. Amplification was performed         on the ABI-5700 using the following thermal profile:     -   50° C. for 2 min     -   95° C. for 10 min     -   and the following for 40 cycles:         -   95° C. for 15 sec         -   60° C. for 1 min     -   2. Quantitation was performed using the ΔC_(T) method in         accordance with the manufactures instructions, and as described         in Example 2 herein.

The results of these experiments are provided in FIG. 8 and described elsewhere herein.

Example 9 Method of Demonstrating Inhibition of SRC Expression by RNAi Reagents Results in Decreased Expression of Predictor Polynucleotides and Polypeptides of the Present Invention as Shown by Western Blotting Assays

As described herein, the EphA2 and caveolin predictor polynucleotides have been shown to be down regulated by BMS-A drug treatment (FIG. 2) through inhibition of the activity of protein tyrosine kinases, such as Src and Src-family kinase. RNAi experiments to block Src expression were performed to see whether it has the same effects on expression of the markers.

Protein expression levels of Src and CAV-1 in Hela cell lines transfected with either negative control RNAi (GFP) or five Src specific RNAi reagents (1-4 and SP, which is smart pool of several RNAi) for 48 hours was assessed. All RNAi reagents were made by Dharmacon, Inc. Total cell lysate were analyzed by Western blot using antibodies for Src (Cat.# 05-184, Upstate Biotechnology Inc.) and for PCNA (Cat.# 610665, BD Transduction, Inc) or antibodies for CAV-1 (Cat.# 610406, BD Transduction, Inc) and PCNA. The PCNA protein level was used as an internal control for protein loading, the level of Src or CAV-1 expression was normalized to the level of PCNA. The percentage of inhibition was calculated by comparing ratio of Src/PCNA or CAV-1/PCNA from each of Src-RNAi transfected cells to the ratio from the negative control, which was transfected by GFP RNAi.

Protocol for Transfection of A549 Cells with RNAi Reagents

-   -   1. Cells were seeded 4×10⁵ per well in DMEM media in 6-well         plates and culture at 37° C. overnight.     -   2. Media was aspirated from the wells and 1 ml of fresh media         without serum and antibiotics was added to each well.     -   3. Each RNAi reagent was diluted to 150 nM in 100 μl of OptiMEM         (Gibco-BRL) for one transfection per well. 4 μl of Lipofectamine         ((Invitrogen) was diluted in 100 μl OptiMEM. The diluted RNAi         reagent was mixed with the Lipofectamine mixture and incubated         at room temperature for 20 minutes to allow formation of complex         between the reagent and the lipid.     -   4. 200 μl of complex was added to each appropriate well         containing 1 ml of fresh media.     -   5. Cells were incubated at 37° C. with transfection media for         4.5 hours, after which the media was removed and fresh growth         media was added. Cells were cultured for 48 hours.     -   6. Media was aspirated, cells were washed with cold 1×PBS and         processed for protein analysis.

Protocol for Protein Lysate Preparation and Western Blotting

-   -   1. Protein samples were collected from each transfection well         with 200 μl RIPA buffer containing protease inhibitor (Roche) on         ice. Lysates were spun for 10 min at 4° C. (12,000 rpm). Samples         were either stored at −20° C. or prepared for loading.     -   2. Protein concentration was determined by the BCA Assay         (Pierce) using BSA for creating a standard curve with a 0.125-2         mg/ml range.     -   3. 10 μg protein for each sample was mixed with an appropriate         amount of 4×LDS Sample Buffer to provide 1×LDS. Water was added         to bring it to a volume of 27 μl. 3 μl of 10× Reducing Buffer         was added to provide a loading volume of 30 μl.     -   4. The mixture was heated at 70° C. for 10 minutes, then placed         on ice. The sample was centrifuged at 12,000 rpm for 5 minutes,         prior to loading.     -   5. Magic Mark standard was run alongside samples at 200V for 35         minutes on a 4-12% NuPAGE Bis-Tris gel using 1×MES Running         Buffer. And 0.25% antioxidant was added to 200 ml for the Upper         Buffer.     -   6. Gel was transferred at 30V for 1 hr to a PVDF membrane in         1×NuPAGE transfer buffer, 20% methanol and 0.1% antioxidant.     -   7. Membranes were blocked overnight in 5% milk in         PBS/1.05%-Tween20.     -   8. Mouse monoclonal antibodies to markers EphA2 (1:300) and Src         (1:250) (Upstate), Caveolin 1 (1:1000) and PCNA (1:500) were         diluted in a blocking buffer (5% milk in 1×PBS/1.05% Tween20),         incubated with membranes at room temperature for 1.5 hours.     -   9. Membranes were washed in PBS/1.05% Tween20 for 5 minutes with         3 changes and then 10 minutes with 3 changes.     -   10. Anti-mouse Horseradish peroxidase conjugate secondary         antibody was diluted (1:10,000) in blocking buffer 1×-PBS/1.05%         Tween-20, add to membrane and rock at RT for a minimum of 30′.     -   11. Blots were again washed in PBS/1.05% Tween20 5 minutes with         3 changes and then 10 minutes with 3 changes.     -   12. Chemiluminescence were performed using Amersham's ECL Plus.         Enough ECL reagent is added to cover the membrane for incubated         for 5 minutes at room temperature. Blot was placed between two         transparency and chemiluminescence detected using Fluor S-Max         (Bio-Rad), 3-5 minutes exposures. Bands were quantitated using         Quantity One software (Bio-Rad).

The results of these experiments are provided in FIG. 9 and described elsewhere herein.

Example 10 Method of Validating Expression Pattern of Predictor Polynucleotides as Measured Using Affymetric Genechip Assays Using RT-PCR Assays

To test whether the gene expression pattern measured by Affymetric Genechip can be cross validated by another technology platform, the expression level of four selected predictor markers (EphA2, EphB2, CAV-1 and CAV-2) was further evaluated by quantitative RT-PCR assays. The RNA utilized for this analysis was obtained from the 23 breast cell lines that were used to originally generate the gene expression profiles that led to the identification of the predictor markers of the present invention.

RT-PCR assays were performed as described in Example 2 herein; while the Affymetric Genechip assays were performed as descrived in Example 1. Both assays were performed in triplicates. The expression of the selected four markers was normalized to the expression of the GAPDH gene.

The relative expression level (relative to MDA-MB-157, set to 1000) of markers for each cell line measured by both Affymetrix Genechip and quantitative RT-PCR are illustrated in FIG. 10 and summarized in Table 13.

Example 11 Method of Demonstrating Protein Expression Levels of Predictor Polypeptides is Correlative with the Predictor Polypeptides RNA Expression Level Using Immunohistochemistry Assays

To test whether the protein level of the cell lines are correlated with RNA expression level, IHC assays were utilized to evaluate the protein expression of selected predictor markers (EphA2 and CAV-1). Five breast cancer cell lines were selected from the 23 cell lines according to their sensitivity to BMS-A compound and used to make slides for IHC assay. A cell array was constructed containing 5 breast cancer cell lines and stained under the same conditions. Hematoxylin counterstain provides a blue nuclear stain to assess cell and tissue morphology. Positive staining is indicated by the presence of a brown chromogen. Both EphA2 and Caveolin-1 antibodies were from Santa Cruz Signal Transduction Lab (Cat #: sc-924 for EphA2 and sc-894 for CAV-1).

Paraffin Block Preparation of Cell Lines

-   -   1. 10⁶ cells were fixed in 1% neutral buffered formalin (NBF) in         a 1.5 ml eppendorf tube and spin at 1500 rpm for 4 min at         microcentrifuge.     -   2. The NBF was carefully removeed, and cells re-suspended in 1         ml PBS.     -   3. Cells were spun at 1500 rpm for 4 min in a microcentrifuge.     -   4. PBS was carefully removed,     -   5. Steps 2, 3 & 4 were repeated.     -   6. Cells were re-suspended in 0.5 ml pre-warmed HistoGel         (Richard-Allan Scientific, Cat# HG-4000).     -   7. Cells were spun at 3000 rpm for 4 min in a microcentrifuge.     -   8. Most of the HistoGel was removed, and the tubes were tapped         to make the cells evenly in the HistoGel.     -   9. Tubes were maintained on ice until the HistoGel hardened         (approximately 30 mins).     -   10. The cell/HistoGel pellet was removed, and wrapped with a         weight paper in a cassette,     -   11. The cassette was placed in 70% Ethanol for Paraffin-embed         and slide processing.

Immunohistochemistry (IHC) Protocol

-   -   1. Slides were de-paraffined by immersing the slides in Xylene         for 5 mins, and repeated one time.     -   2. Slides were re-hydrated with 2×100% Ethanol, 2×95% Ethanol,         and 75% Ethanol, 3 min each.     -   3. Slides were washed with dH2O, 2 times at RT., 5 mins each         time.     -   4. Antigen retrieval was performed by using BioGenex         EZ-Retriever Microwave, 250 ml of Citra, Citra Plus & AR10 in 3         containers, and slides were then heated to 95° C. for 15 mins,     -   5. Slides were cooled at room temperature for 5 mins and rinsed         with tap water for about 5 mins.     -   6. The protocol on i6000 autostainer was set-up.     -   7. A Pap-Pen was used to mark the tissue area for reagents and         the slides were then placed on the i6000 autostainer     -   8. The IHC protocol was run by using the following steps on the         i6000 autostainer.     -   The “Peroxidase block” was applied for 5 mins., followed by         rinse with IHC wash buffer, 3 times     -   The antibodies were applied to the slides         -   Caveolin-1 (N-20), 0.5 μg/ml         -   EphA2 (C-20), 0.5 μg/ml         -   Negative control, Normal Rabbit IgG, 5 μg/ml,     -   Slides were incubated for 1 hr at RT.     -   Slides were washed by rinsing them 3 times with IHC wash buffer,     -   The “Labelled Polymer-HRP, anti-rabbit” was added to the slides         and incubated for 30 mins.,     -   Slides were rinsed with IHC wash buffer, 3 times.     -   The DAB chromogen substrates were added, and allowed to develop         for 5 mins,     -   Slides were washed by rinsing them with dH2O for 5 times at RT.,     -   Slides were counterstained with Hematoxylin, 1 min, RT.     -   Slides were washed by rinsing them with dH2O for 5 times at RT.,     -   Slides were removed from the i6000 autostainer and placed in the         staining container with dH2O.     -   Slides were dehydrated with 70% Ethanol, 95% Ethanol, 2×100%         Ethanol, 2 min each.     -   Slides were washed in Xylene 2× for 2 min.     -   Coverslips were sealed with Cytoseal Mounting Medium.

The results of these experiments are provided in FIG. 11 and described elsewhere herein.

BRIEF DESCRIPTION OF THE SEQUENCE LISTING

Incorporated herein by reference in its entirety is a Sequence Listing, comprising SEQ ID NO:1 through SEQ ID NO:572, which include nucleic acid and amino acid sequences of the protein tyrosine kinase biomarkers as presented in Table 2 herein and the nucleotide sequences of forward and reverse primer pairs for the polynucleotide markers, probes, and RNAi reagents as described herein. The Sequence Listing is contained on a compact disc, i.e., CD-ROM, three identical copies of which are filed herewith. The Sequence Listing, in IBM/PC MS-DOS text format, was first created on Feb. 18, 2005, and is 900 KB in size.

The contents of all patents, patent applications, published PCT applications and articles, books, references, reference manuals, abstracts, the Sequence Listing, and internet websites cited herein are hereby incorporated by reference in their entirety to more fully describe the state of the art to which the invention pertains.

As various changes can be made in the above-described subject matter without departing from the scope and spirit of the present invention, it is intended that all subject matter contained in the above description, or defined in the appended claims, be interpreted as descriptive and illustrative of the present invention. Many modifications and variations of the present invention are possible in light of the above teachings. 

1. A method of identifying breast cancer cells that are either resistant or sensitive to inhibition of cellular proliferation by a protein tyrosine kinase inhibitor comprising the steps of: (a) determining the expression profile of a plurality of informative genes from said breast cancer cells by measuring the gene expression products of said plurality of informative genes; (b) normalizing the values of the expression profile of said plurality of informative genes to an internal control gene that is GADPH or an other housekeeping gene; (c) comparing the normalized values of said expression profile of said plurality of informative genes to the average normalized expression value of said plurality of informative genes in a panel of control breast cancer cells, wherein said panel of control breast cancer cells consist of a plurality of breast cancer cells that are sensitive and a plurality of breast cancer cells that are resistant to said protein tyrosine kinase inhibitor; and (d) predicting whether said breast cancer cells are resistant or sensitive to inhibition of cellular proliferation by the protein tyrosine kinase inhibitor, wherein said plurality of informative genes consists of: EphA2; caveolin 1; caveolin 2; annexin A2; polymerase I and transcript release factor; and insulin-like growth factor binding protein 2, wherein said protein tyrosine kinase inhibitor is an inhibitor of Src, Fgr, Fyn, Yes, Blk, Hck Lck, Lyn, BCR-ABL, PDGFR, c-Kit, and EphA2, and wherein an expression level of one or more of said gene expression products from EphA2; caveolin 1; caveolin 2; annexin A2; or polymerase I and transcript release factor in said breast cancer cells that is higher, relative to the average expression level of said gene expression product in said panel of control breast cancer cells, or wherein an expression level of insulin-like growth factor binding protein 2 in said breast cancer cells that is lower, relative to the average expression level of said gene expression product in said panel of control breast cancer cells, is indicative of sensitivity to the protein tyrosine kinase inhibitor, while an expression level of one or more of said gene expression products from EphA2; caveolin 1; caveolin 2; annexin A2; or polymerase I and transcript release factor in said breast cancer cancer that is lower, relative to the average expression level of said gene expression product in said panel of control breast cancer cells, or wherein an expression level of insulin-like growth factor binding protein 2 in said breast cancer cells that is higher, relative to the average expression level of said gene expression product in said panel of control breast cancer cells, is indicative of resistance to the protein tyrosine kinase inhibitor. 